new w-statistic()
- Source:
Methods
(static) arrAverage(arr) → {Number}
- Description:
計算陣列內有效數字之平均值
Unit Test: Github
- Source:
Example
let arr
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrAverage(arr))
// => 1.5
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrAverage(arr))
// => 3.3Parameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
Returns:
回傳平均值
- Type
- Number
(async, static) arrAverageWithLogNormCI(arr, p, mode) → {Number}
- Description:
基於Student-T累加分布之信賴水準(p)以及指定左右單尾條件下，計算樣本平均值。Student-T需用於常態分佈樣本，故數據是取log後為常態分佈才能以此計算，而於取log後座標算出樣本平均值，會再取其指數(exp)值回傳。此時左尾代表樣本平均值可小於等於母數平均值，而右尾代表樣本平均值可大於等於母數平均值
Unit Test: Github
- Source:
Example
async function test() {
let arr
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithLogNormCI(arr, 0.95))
// => [ 27.615050054890812, 26.794611985184215 ]
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithLogNormCI(arr, 0.95, 'upper-tail'))
// => 41.610938902127394
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithLogNormCI(arr, 0.95, 'lower-tail'))
// => 17.782212338746568
arr = [18.7261764705882, 18.6629411764705, 19.3983050847457, 18.5099999999999, 18.9986446886446, 18.9083937823834, 19.1957837837837, 19.0423529411764, 19.2320588235294, 18.8526470588235, 18.7982198952879, 19.0423529411764, 19.075, 18.945238095238, 20.6691240875912]
console.log(await arrAverageWithLogNormCI(arr, 0.95, 'upper-tail'))
// => 19.28628574730297
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithLogNormCI(arr, 0.25))
// => [ 36.223415575653085, 20.42696800987406 ]
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithLogNormCI(arr, 0.5))
// => [ 32.05361593350904, 23.084277065874097 ]
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithLogNormCI(arr, 0.75))
// => [ 29.373829998564737, 25.190264640613567 ]
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(await arrAverageWithLogNormCI(arr, 0.50))
// => [ 1.7639684225556826, 0.6249032382061773 ]
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(await arrAverageWithLogNormCI(arr, 0.50))
// => [ 1.7639684225556826, 0.6249032382061773 ]
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Default | Description |
|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
|
p |
Number | 輸入信賴水準浮點數，需介於0至1之間 |
|
mode |
String |
two-tailed
|
輸入檢定模式字串，可選'two-tailed'、'upper-tail'、'lower-tail'，預設'two-tailed' |
Returns:
回傳樣本平均值
- Type
- Number
(async, static) arrAverageWithNormCI(arr, p, mode) → {Number}
- Description:
基於Student-T累加分布之信賴水準(p)以及指定左右單尾條件下，計算樣本平均值。Student-T需用於常態分佈樣本。此時左尾代表樣本平均值可小於等於母數平均值，而右尾代表樣本平均值可大於等於母數平均值
Unit Test: Github
- Source:
Example
async function test() {
let arr
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithNormCI(arr, 0.95))
// => [ 33.48954903620701, 32.87408732742935 ]
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithNormCI(arr, 0.95, 'upper-tail'))
// => 41.85625495776645
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithNormCI(arr, 0.95, 'lower-tail'))
// => 24.507381405869904
arr = [18.7261764705882, 18.6629411764705, 19.3983050847457, 18.5099999999999, 18.9986446886446, 18.9083937823834, 19.1957837837837, 19.0423529411764, 19.2320588235294, 18.8526470588235, 18.7982198952879, 19.0423529411764, 19.075, 18.945238095238, 20.6691240875912]
console.log(await arrAverageWithNormCI(arr, 0.95, 'upper-tail'))
// => 19.297020890880212
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithNormCI(arr, 0.25))
// => [ 39.026745129035845, 27.336891234600518 ]
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithNormCI(arr, 0.5))
// => [ 36.53111791211017, 29.832518451526187 ]
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(await arrAverageWithNormCI(arr, 0.75))
// => [ 34.74951166569791, 31.614124697938454 ]
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(await arrAverageWithNormCI(arr, 0.50))
// => [ 2.5700668400787645, 0.4299331599212357 ]
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(await arrAverageWithNormCI(arr, 0.50))
// => [ 5.011682286477105, 1.5883177135228952 ]
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Default | Description |
|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
|
p |
Number | 輸入信賴水準浮點數，需介於0至1之間 |
|
mode |
String |
two-tailed
|
輸入檢定模式字串，可選'two-tailed'、'upper-tail'、'lower-tail'，預設'two-tailed' |
Returns:
回傳樣本平均值
- Type
- Number
(static) arrCount(arr) → {Array}
- Description:
計算陣列內有效字串依照不重複值進行群組化後，回傳各值之出現次數值
Unit Test: Github
- Source:
Example
let arr
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, 'abc', '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrCount(arr))
// => [
// { key: '2.5', count: 2 },
// { key: '0.1', count: 2 },
// { key: '-0.1', count: 2 },
// { key: '-1', count: 2 },
// { key: '-2.5', count: 2 },
// { key: 'abc', count: 2 },
// { key: '1', count: 2 },
// { key: '0', count: 2 },
// { key: 'xyz', count: 1 },
// { key: '22.5', count: 1 }
// ]
arr = ['abc', '0', 0, 'abc', '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrCount(arr))
// => [
// { key: '2.5', count: 2 },
// { key: '0.1', count: 2 },
// { key: 'abc', count: 2 },
// { key: '1', count: 2 },
// { key: '0', count: 2 },
// { key: 'xyz', count: 1 },
// { key: '22.5', count: 1 }
//]Parameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效字串(或為字串的數字)進行計算 |
Returns:
回傳各值出現次數值陣列
- Type
- Array
(async, static) arrGammaFit(arr) → {Object}
- Description:
計算擬合Gamma分布之參數
Unit Test: Github
- Source:
Example
async function test() {
let arr
let r
arr = [12, 36, 9, 13, 6, 17, 7, 12, 31, 57, 44, 32, 16, 11, 10, 38, 31, 28, 26, 7, 16, 16, 16, 13, 7, 8, 12, 17, 11, 20, 7, 6, 14, 7, 37, 11, 7, 8, 8, 32, 29, 52, 20, 6, 11, 12, 33, 48, 10, 27, 11, 24, 17, 11, 23, 20, 13, 16, 16, 17, 13, 15, 13, 26, 11, 13, 29, 18, 18, 13, 11, 12, 9, 17, 19, 14, 19, 9, 37, 32, 14, 20, 13, 22, 12, 14, 33, 15, 20, 37, 24, 19, 15, 15, 5, 11, 13, 60, 39, 17, 6, 18, 40, 21, 18, 17, 12, 12, 10, 39, 27, 10, 8, 44, 36, 18, 11, 8, 13, 9, 25, 11, 10, 55, 54, 13, 8, 19, 38, 9, 17, 14, 9, 12, 54, 22, 11, 19, 50, 18, 12, 40, 52, 12, 15, 7, 12, 15, 18, 19, 11, 43, 23, 14, 25, 32, 23, 15, 12, 20, 14, 10, 12, 24, 50, 40, 16, 14, 9, 27, 9, 11, 17, 19, 12, 17, 14, 5, 24, 22, 60, 20, 9, 11, 11, 6, 7, 8, 31, 10, 12, 9, 11, 26, 14, 7, 14, 57, 19, 9, 10, 9, 19, 19, 15, 21, 48, 23, 26, 14, 46, 51, 10, 10, 9, 7, 19, 46, 27, 18, 12, 10, 36, 15, 5, 11, 13, 21, 15, 15, 16, 29, 44, 42, 7, 14, 9, 6, 22, 24, 18, 39, 7, 50, 33, 11, 20, 17, 18, 48, 8, 21, 20, 12, 41, 11, 18, 11, 58, 18, 21, 23, 12, 67, 35]
r = await arrGammaFit(arr, {
n: 69,
min: 1,
max: 70,
})
console.log(r)
// => {
// shape: 3.8362965388539396,
// scale: 4.074897568773075,
// arrPdf: [
// [ 1.5, 0, 0.002034542900938358 ],
// [ 2.5, 0, 0.006778251528074013 ],
// [ 3.5, 0, 0.013772161615714786 ],
// [ 4.5, 0.011320754716981131, 0.02197810173523445 ],
// [ 5.5, 0.022641509433962263, 0.030380569392341527 ],
// [ 6.5, 0.045283018867924525, 0.03817623569640994 ],
// [ 7.5, 0.03018867924528302, 0.044821355259143096 ],
// [ 8.5, 0.052830188679245285, 0.05001282903727686 ],
// [ 9.5, 0.04150943396226415, 0.053642598229888455 ],
// [ 10.5, 0.07924528301886792, 0.05574595886606071 ],
// [ 11.5, 0.07169811320754717, 0.05645381775460518 ],
// [ 12.5, 0.045283018867924525, 0.05595305000100274 ],
// [ 13.5, 0.04905660377358491, 0.05445596204835303 ],
// [ 14.5, 0.04150943396226415, 0.05217827444112463 ],
// [ 15.5, 0.03018867924528302, 0.04932434550769117 ],
// [ 16.5, 0.04150943396226415, 0.04607816130381367 ],
// [ 17.5, 0.045283018867924525, 0.04259868048491963 ],
// [ 18.5, 0.04150943396226415, 0.03901830570786497 ],
// [ 19.5, 0.033962264150943396, 0.03544347629738162 ],
// [ 20.5, 0.018867924528301886, 0.031956597426761706 ],
// [ 21.5, 0.01509433962264151, 0.028618718038250914 ],
// [ 22.5, 0.018867924528301886, 0.025472535008409646 ],
// [ 23.5, 0.018867924528301886, 0.0225454335944075 ],
// [ 24.5, 0.007547169811320755, 0.019852376582105462 ],
// [ 25.5, 0.01509433962264151, 0.017398531002249633 ],
// [ 26.5, 0.01509433962264151, 0.0151815764197815 ],
// [ 27.5, 0.0037735849056603774, 0.013193677058112446 ],
// [ 28.5, 0.011320754716981131, 0.011423125308268597 ],
// [ 29.5, 0, 0.009855679783012123 ],
// [ 30.5, 0.011320754716981131, 0.008475629675587867 ],
// [ 31.5, 0.01509433962264151, 0.007266620869423741 ],
// [ 32.5, 0.011320754716981131, 0.006212279625757307 ],
// [ 33.5, 0, 0.005296667950862123 ],
// [ 34.5, 0.0037735849056603774, 0.004504601786645908 ],
// [ 35.5, 0.011320754716981131, 0.0038218595954222644 ],
// [ 36.5, 0.011320754716981131, 0.0032353051434718273 ],
// [ 37.5, 0.007547169811320755, 0.0027329446040823616 ],
// [ 38.5, 0.011320754716981131, 0.0023039346675539146 ],
// [ 39.5, 0.011320754716981131, 0.001938555255357194 ],
// [ 40.5, 0.0037735849056603774, 0.0016281577276447906 ],
// [ 41.5, 0.0037735849056603774, 0.0013650971518721555 ],
// [ 42.5, 0.0037735849056603774, 0.0011426552473936045 ],
// [ 43.5, 0.011320754716981131, 0.000954959005617501 ],
// [ 44.5, 0, 0.0007968986702454505 ],
// [ 45.5, 0.007547169811320755, 0.0006640477078460918 ],
// [ 46.5, 0, 0.0005525865668975019 ],
// [ 47.5, 0.011320754716981131, 0.0004592313773931834 ],
// [ 48.5, 0, 0.00038116825056312947 ],
// [ 49.5, 0.011320754716981131, 0.0003159934705381866 ],
// [ 50.5, 0.0037735849056603774, 0.00026165960216326697 ],
// [ 51.5, 0.007547169811320755, 0.00021642735070210298 ],
// [ 52.5, 0, 0.00017882288240340192 ],
// [ 53.5, 0.007547169811320755, 0.00014760023544158093 ],
// [ 54.5, 0.0037735849056603774, 0.00012170840693236135 ],
// [ 55.5, 0, 0.0001002626841944302 ],
// [ 56.5, 0.007547169811320755, 0.00008251978977290701 ],
// [ 57.5, 0.0037735849056603774, 0.00006785642416854554 ],
// [ 58.5, 0, 0.000055750813268511874 ],
// [ 59.5, 0.007547169811320755, 0.00004576689576865875 ],
// [ 60.5, 0, 0.000037540816896368505 ],
// [ 61.5, 0, 0.00003076942665494607 ],
// [ 62.5, 0, 0.000025200512318922518 ],
// [ 63.5, 0, 0.000020624525132396522 ],
// [ 64.5, 0, 0.000016867589533140664 ],
// [ 65.5, 0, 0.000013785609413643612 ],
// [ 66.5, 0.0037735849056603774, 0.000011259309780444045 ],
// [ 67.5, 0, 0.000009190073653789351 ],
// [ 68.5, 0, 0.000007496453216403037 ],
// [ 69.5, 0, 0.000006111251186318431 ]
// ],
// arrCounts: [
// [ 1.5, 0, 0.5391538687486649 ],
// [ 2.5, 0, 1.7962366549396136 ],
// [ 3.5, 0, 3.6496228281644183 ],
// [ 4.5, 3, 5.8241969598371295 ],
// [ 5.5, 6, 8.050850888970505 ],
// [ 6.5, 12, 10.116702459548634 ],
// [ 7.5, 8, 11.87765914367292 ],
// [ 8.5, 14, 13.253399694878366 ],
// [ 9.5, 11, 14.215288530920441 ],
// [ 10.5, 21, 14.772679099506087 ],
// [ 11.5, 19, 14.960261704970373 ],
// [ 12.5, 12, 14.827558250265724 ],
// [ 13.5, 13, 14.430829942813553 ],
// [ 14.5, 11, 13.827242726898026 ],
// [ 15.5, 8, 13.07095155953816 ],
// [ 16.5, 11, 12.210712745510621 ],
// [ 17.5, 12, 11.288650328503703 ],
// [ 18.5, 11, 10.339851012584218 ],
// [ 19.5, 9, 9.39252121880613 ],
// [ 20.5, 5, 8.468498318091852 ],
// [ 21.5, 4, 7.583960280136492 ],
// [ 22.5, 5, 6.750221777228556 ],
// [ 23.5, 5, 5.9745399025179875 ],
// [ 24.5, 2, 5.2608797942579475 ],
// [ 25.5, 4, 4.610610715596152 ],
// [ 26.5, 4, 4.023117751242098 ],
// [ 27.5, 1, 3.496324420399798 ],
// [ 28.5, 3, 3.027128206691178 ],
// [ 29.5, 0, 2.6117551424982124 ],
// [ 30.5, 3, 2.2460418640307847 ],
// [ 31.5, 4, 1.9256545303972914 ],
// [ 32.5, 3, 1.6462541008256864 ],
// [ 33.5, 0, 1.4036170069784626 ],
// [ 34.5, 1, 1.1937194734611656 ],
// [ 35.5, 3, 1.0127927927869 ],
// [ 36.5, 3, 0.8573558630200342 ],
// [ 37.5, 2, 0.7242303200818259 ],
// [ 38.5, 3, 0.6105426869017874 ],
// [ 39.5, 3, 0.5137171426696564 ],
// [ 40.5, 1, 0.4314617978258695 ],
// [ 41.5, 1, 0.3617507452461212 ],
// [ 42.5, 1, 0.3028036405593052 ],
// [ 43.5, 3, 0.25306413648863774 ],
// [ 44.5, 0, 0.2111781476150444 ],
// [ 45.5, 2, 0.17597264257921433 ],
// [ 46.5, 0, 0.146435440227838 ],
// [ 47.5, 3, 0.12169631500919359 ],
// [ 48.5, 0, 0.10100958639922931 ],
// [ 49.5, 3, 0.08373826969261944 ],
// [ 50.5, 1, 0.06933979457326575 ],
// [ 51.5, 2, 0.05735324793605729 ],
// [ 52.5, 0, 0.04738806383690151 ],
// [ 53.5, 2, 0.03911406239201894 ],
// [ 54.5, 1, 0.03225272783707576 ],
// [ 55.5, 0, 0.026569611311524 ],
// [ 56.5, 2, 0.021867744289820357 ],
// [ 57.5, 1, 0.017981952404664568 ],
// [ 58.5, 0, 0.014773965516155646 ],
// [ 59.5, 2, 0.012128227378694569 ],
// [ 60.5, 0, 0.009948316477537654 ],
// [ 61.5, 0, 0.008153898063560708 ],
// [ 62.5, 0, 0.006678135764514467 ],
// [ 63.5, 0, 0.005465499160085078 ],
// [ 64.5, 0, 0.004469911226282276 ],
// [ 65.5, 0, 0.0036531864946155574 ],
// [ 66.5, 1, 0.002983717091817672 ],
// [ 67.5, 0, 0.002435369518254178 ],
// [ 68.5, 0, 0.0019865601023468047 ],
// [ 69.5, 0, 0.0016194815643743841 ]
// ],
// dx: 1,
// bs: [
// { min: 1, max: 2, avg: 1.5, arr: [], counts: 0, pdf: 0 },
// { min: 2, max: 3, avg: 2.5, arr: [], counts: 0, pdf: 0 },
// { min: 3, max: 4, avg: 3.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 4,
// max: 5,
// avg: 4.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 5,
// max: 6,
// avg: 5.5,
// arr: [Array],
// counts: 6,
// pdf: 0.022641509433962263
// },
// {
// min: 6,
// max: 7,
// avg: 6.5,
// arr: [Array],
// counts: 12,
// pdf: 0.045283018867924525
// },
// {
// min: 7,
// max: 8,
// avg: 7.5,
// arr: [Array],
// counts: 8,
// pdf: 0.03018867924528302
// },
// {
// min: 8,
// max: 9,
// avg: 8.5,
// arr: [Array],
// counts: 14,
// pdf: 0.052830188679245285
// },
// {
// min: 9,
// max: 10,
// avg: 9.5,
// arr: [Array],
// counts: 11,
// pdf: 0.04150943396226415
// },
// {
// min: 10,
// max: 11,
// avg: 10.5,
// arr: [Array],
// counts: 21,
// pdf: 0.07924528301886792
// },
// {
// min: 11,
// max: 12,
// avg: 11.5,
// arr: [Array],
// counts: 19,
// pdf: 0.07169811320754717
// },
// {
// min: 12,
// max: 13,
// avg: 12.5,
// arr: [Array],
// counts: 12,
// pdf: 0.045283018867924525
// },
// {
// min: 13,
// max: 14,
// avg: 13.5,
// arr: [Array],
// counts: 13,
// pdf: 0.04905660377358491
// },
// {
// min: 14,
// max: 15,
// avg: 14.5,
// arr: [Array],
// counts: 11,
// pdf: 0.04150943396226415
// },
// {
// min: 15,
// max: 16,
// avg: 15.5,
// arr: [Array],
// counts: 8,
// pdf: 0.03018867924528302
// },
// {
// min: 16,
// max: 17,
// avg: 16.5,
// arr: [Array],
// counts: 11,
// pdf: 0.04150943396226415
// },
// {
// min: 17,
// max: 18,
// avg: 17.5,
// arr: [Array],
// counts: 12,
// pdf: 0.045283018867924525
// },
// {
// min: 18,
// max: 19,
// avg: 18.5,
// arr: [Array],
// counts: 11,
// pdf: 0.04150943396226415
// },
// {
// min: 19,
// max: 20,
// avg: 19.5,
// arr: [Array],
// counts: 9,
// pdf: 0.033962264150943396
// },
// {
// min: 20,
// max: 21,
// avg: 20.5,
// arr: [Array],
// counts: 5,
// pdf: 0.018867924528301886
// },
// {
// min: 21,
// max: 22,
// avg: 21.5,
// arr: [Array],
// counts: 4,
// pdf: 0.01509433962264151
// },
// {
// min: 22,
// max: 23,
// avg: 22.5,
// arr: [Array],
// counts: 5,
// pdf: 0.018867924528301886
// },
// {
// min: 23,
// max: 24,
// avg: 23.5,
// arr: [Array],
// counts: 5,
// pdf: 0.018867924528301886
// },
// {
// min: 24,
// max: 25,
// avg: 24.5,
// arr: [Array],
// counts: 2,
// pdf: 0.007547169811320755
// },
// {
// min: 25,
// max: 26,
// avg: 25.5,
// arr: [Array],
// counts: 4,
// pdf: 0.01509433962264151
// },
// {
// min: 26,
// max: 27,
// avg: 26.5,
// arr: [Array],
// counts: 4,
// pdf: 0.01509433962264151
// },
// {
// min: 27,
// max: 28,
// avg: 27.5,
// arr: [Array],
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 28,
// max: 29,
// avg: 28.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// { min: 29, max: 30, avg: 29.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 30,
// max: 31,
// avg: 30.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 31,
// max: 32,
// avg: 31.5,
// arr: [Array],
// counts: 4,
// pdf: 0.01509433962264151
// },
// {
// min: 32,
// max: 33,
// avg: 32.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// { min: 33, max: 34, avg: 33.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 34,
// max: 35,
// avg: 34.5,
// arr: [Array],
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 35,
// max: 36,
// avg: 35.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 36,
// max: 37,
// avg: 36.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 37,
// max: 38,
// avg: 37.5,
// arr: [Array],
// counts: 2,
// pdf: 0.007547169811320755
// },
// {
// min: 38,
// max: 39,
// avg: 38.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 39,
// max: 40,
// avg: 39.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 40,
// max: 41,
// avg: 40.5,
// arr: [Array],
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 41,
// max: 42,
// avg: 41.5,
// arr: [Array],
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 42,
// max: 43,
// avg: 42.5,
// arr: [Array],
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 43,
// max: 44,
// avg: 43.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// { min: 44, max: 45, avg: 44.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 45,
// max: 46,
// avg: 45.5,
// arr: [Array],
// counts: 2,
// pdf: 0.007547169811320755
// },
// { min: 46, max: 47, avg: 46.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 47,
// max: 48,
// avg: 47.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// { min: 48, max: 49, avg: 48.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 49,
// max: 50,
// avg: 49.5,
// arr: [Array],
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 50,
// max: 51,
// avg: 50.5,
// arr: [Array],
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 51,
// max: 52,
// avg: 51.5,
// arr: [Array],
// counts: 2,
// pdf: 0.007547169811320755
// },
// { min: 52, max: 53, avg: 52.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 53,
// max: 54,
// avg: 53.5,
// arr: [Array],
// counts: 2,
// pdf: 0.007547169811320755
// },
// {
// min: 54,
// max: 55,
// avg: 54.5,
// arr: [Array],
// counts: 1,
// pdf: 0.0037735849056603774
// },
// { min: 55, max: 56, avg: 55.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 56,
// max: 57,
// avg: 56.5,
// arr: [Array],
// counts: 2,
// pdf: 0.007547169811320755
// },
// {
// min: 57,
// max: 58,
// avg: 57.5,
// arr: [Array],
// counts: 1,
// pdf: 0.0037735849056603774
// },
// { min: 58, max: 59, avg: 58.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 59,
// max: 60,
// avg: 59.5,
// arr: [Array],
// counts: 2,
// pdf: 0.007547169811320755
// },
// { min: 60, max: 61, avg: 60.5, arr: [], counts: 0, pdf: 0 },
// { min: 61, max: 62, avg: 61.5, arr: [], counts: 0, pdf: 0 },
// { min: 62, max: 63, avg: 62.5, arr: [], counts: 0, pdf: 0 },
// { min: 63, max: 64, avg: 63.5, arr: [], counts: 0, pdf: 0 },
// { min: 64, max: 65, avg: 64.5, arr: [], counts: 0, pdf: 0 },
// { min: 65, max: 66, avg: 65.5, arr: [], counts: 0, pdf: 0 },
// {
// min: 66,
// max: 67,
// avg: 66.5,
// arr: [Array],
// counts: 1,
// pdf: 0.0037735849056603774
// },
// { min: 67, max: 68, avg: 67.5, arr: [], counts: 0, pdf: 0 },
// { min: 68, max: 69, avg: 68.5, arr: [], counts: 0, pdf: 0 },
// { min: 69, max: 70, avg: 69.5, arr: [], counts: 0, pdf: 0 }
// ]
// }
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
Returns:
回傳參數物件
- Type
- Object
(async, static) arrGammaHist(arr, optopt) → {Number}
- Description:
基於Gamma分布計算陣列數據分組直方圖、統計與趨勢線數據
Unit Test: Github
- Source:
Example
async function test() {
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Attributes | Default | Description | ||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
||||||||||||||||||||||||||||||||
opt |
Object |
<optional> |
{}
|
輸入設定物件，預設{} Properties
|
Returns:
回傳反函數值
- Type
- Number
(async, static) arrGammaInv(arr, ratio) → {Number}
- Description:
基於Gamma累加分布計算指定位置之反函數值
Unit Test: Github
- Source:
Example
async function test() {
let arr
let r
arr = [12, 36, 9, 13, 6, 17, 7, 12, 31, 57, 44, 32, 16, 11, 10, 38, 31, 28, 26, 7, 16, 16, 16, 13, 7, 8, 12, 17, 11, 20, 7, 6, 14, 7, 37, 11, 7, 8, 8, 32, 29, 52, 20, 6, 11, 12, 33, 48, 10, 27, 11, 24, 17, 11, 23, 20, 13, 16, 16, 17, 13, 15, 13, 26, 11, 13, 29, 18, 18, 13, 11, 12, 9, 17, 19, 14, 19, 9, 37, 32, 14, 20, 13, 22, 12, 14, 33, 15, 20, 37, 24, 19, 15, 15, 5, 11, 13, 60, 39, 17, 6, 18, 40, 21, 18, 17, 12, 12, 10, 39, 27, 10, 8, 44, 36, 18, 11, 8, 13, 9, 25, 11, 10, 55, 54, 13, 8, 19, 38, 9, 17, 14, 9, 12, 54, 22, 11, 19, 50, 18, 12, 40, 52, 12, 15, 7, 12, 15, 18, 19, 11, 43, 23, 14, 25, 32, 23, 15, 12, 20, 14, 10, 12, 24, 50, 40, 16, 14, 9, 27, 9, 11, 17, 19, 12, 17, 14, 5, 24, 22, 60, 20, 9, 11, 11, 6, 7, 8, 31, 10, 12, 9, 11, 26, 14, 7, 14, 57, 19, 9, 10, 9, 19, 19, 15, 21, 48, 23, 26, 14, 46, 51, 10, 10, 9, 7, 19, 46, 27, 18, 12, 10, 36, 15, 5, 11, 13, 21, 15, 15, 16, 29, 44, 42, 7, 14, 9, 6, 22, 24, 18, 39, 7, 50, 33, 11, 20, 17, 18, 48, 8, 21, 20, 12, 41, 11, 18, 11, 58, 18, 21, 23, 12, 67, 35]
r = await arrGammaInv(arr, 0.5, {
n: 69,
min: 1,
max: 70,
})
console.log(r.inv)
// => 14.297217114904852
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
ratio |
Number | 輸入指定位置浮點數，需介於0至1之間 |
Returns:
回傳反函數值
- Type
- Number
(static) arrGeometricAverage(arr) → {Number}
- Description:
計算陣列內有效數字之幾何平均值
Unit Test: Github
- Source:
Example
let arr
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrGeometricAverage(arr))
// => 1.0499093195835956
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrGeometricAverage(arr))
// => 1.0499093195835956Parameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
Returns:
回傳幾何平均值
- Type
- Number
(static) arrGeometricStd(arr) → {Number}
- Description:
計算陣列內有效數字之幾何標準差
Unit Test: Github
- Source:
Example
let arr
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrGeometricStd(arr))
// => 6.774243857996147
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrGeometricStd(arr))
// => 6.774243857996147Parameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
Returns:
回傳幾何標準差
- Type
- Number
(async, static) arrLogNormHist(arr, optopt) → {Number}
- Description:
基於對數常態分布計算陣列數據分組直方圖、統計與趨勢線數據
Unit Test: Github
- Source:
Example
async function test() {
let arr
let r
arr = [13.8, 19.5, 16.7, 14.3, 17.5, 14.5, 12.6, 15.6, 8.9, 13.3, 17.1, 15, 16.3, 18.3, 18.7, 16.7, 20.9, 12.3, 22.3, 14.6, 20.1, 16.7, 16.8, 24.2, 21.2, 20.7, 18.6, 18.3, 15.9, 17.2, 18.8, 16.3, 20.5, 14.7, 17.5, 24.1, 14.6, 21.1, 17, 19.6, 21.2, 16, 16.5, 9.3, 16.2, 14.9, 16.3, 13.9, 18.4, 19.2, 24.6, 20.2, 12.8, 12.9, 14.1, 18.5, 13.4, 17.1, 9.9, 21.9, 19.6, 18.3, 19.7, 16.6, 21.7, 11.8, 15.9, 11.4, 14.3, 17.4, 16.4, 20.7, 18.6, 22, 17.9, 16.3, 15.4, 17.2, 17.3, 18.3, 16.8, 20.9, 15, 15.1, 18.6, 17.5, 14.7, 17.4, 13.8, 18.3, 17.2, 13.4, 12.5, 22.8, 18.6, 16.3, 16.1, 15.7, 20.8, 16.4]
r = await arrLogNormHist(arr, {
n: 10,
min: 12,
max: 23,
})
console.log(r)
// => {
// avg: 17.048000000000002,
// std: 3.1686749612576244,
// avg_geo: 16.741131283482233,
// avg_log: 2.817868642436364,
// std_log: 0.19557811714294832,
// arr: [
// 13.8, 19.5, 16.7, 14.3, 17.5, 14.5, 12.6, 15.6, 8.9, 13.3,
// 17.1, 15, 16.3, 18.3, 18.7, 16.7, 20.9, 12.3, 22.3, 14.6,
// 20.1, 16.7, 16.8, 24.2, 21.2, 20.7, 18.6, 18.3, 15.9, 17.2,
// 18.8, 16.3, 20.5, 14.7, 17.5, 24.1, 14.6, 21.1, 17, 19.6,
// 21.2, 16, 16.5, 9.3, 16.2, 14.9, 16.3, 13.9, 18.4, 19.2,
// 24.6, 20.2, 12.8, 12.9, 14.1, 18.5, 13.4, 17.1, 9.9, 21.9,
// 19.6, 18.3, 19.7, 16.6, 21.7, 11.8, 15.9, 11.4, 14.3, 17.4,
// 16.4, 20.7, 18.6, 22, 17.9, 16.3, 15.4, 17.2, 17.3, 18.3,
// 16.8, 20.9, 15, 15.1, 18.6, 17.5, 14.7, 17.4, 13.8, 18.3,
// 17.2, 13.4, 12.5, 22.8, 18.6, 16.3, 16.1, 15.7, 20.8, 16.4
// ],
// min: 12,
// max: 23.000000000000007,
// barWidth: 1.0999999999999996,
// ratioForCountToPdf: 0.00988142292490119,
// bins: [
// {
// min: 12,
// max: 13.1,
// avg: 12.55,
// arr: [Array],
// counts: 5,
// pdf: 0.04940711462450595
// },
// {
// min: 13.1,
// max: 14.2,
// avg: 13.649999999999999,
// arr: [Array],
// counts: 7,
// pdf: 0.06916996047430833
// },
// {
// min: 14.2,
// max: 15.299999999999999,
// avg: 14.75,
// arr: [Array],
// counts: 11,
// pdf: 0.10869565217391308
// },
// {
// min: 15.299999999999999,
// max: 16.4,
// avg: 15.849999999999998,
// arr: [Array],
// counts: 15,
// pdf: 0.14822134387351785
// },
// {
// min: 16.4,
// max: 17.5,
// avg: 16.95,
// arr: [Array],
// counts: 19,
// pdf: 0.1877470355731226
// },
// {
// min: 17.5,
// max: 18.6,
// avg: 18.05,
// arr: [Array],
// counts: 12,
// pdf: 0.11857707509881428
// },
// {
// min: 18.6,
// max: 19.700000000000003,
// avg: 19.150000000000002,
// arr: [Array],
// counts: 7,
// pdf: 0.06916996047430833
// },
// {
// min: 19.700000000000003,
// max: 20.800000000000004,
// avg: 20.250000000000004,
// arr: [Array],
// counts: 6,
// pdf: 0.05928853754940714
// },
// {
// min: 20.800000000000004,
// max: 21.900000000000006,
// avg: 21.350000000000005,
// arr: [Array],
// counts: 7,
// pdf: 0.06916996047430833
// },
// {
// min: 21.900000000000006,
// max: 23.000000000000007,
// avg: 22.450000000000006,
// arr: [Array],
// counts: 3,
// pdf: 0.02964426877470357
// }
// ],
// curves: [
// { x: 8.9, pdf: 0.0003700715564882641 },
// { x: 8.990947415368343, pdf: 0.0004371517692405818 },
// { x: 9.082824205159403, pdf: 0.0005149975464899293 },
// { x: 9.17563986647449, pdf: 0.0006050683906353664 },
// { x: 9.269403993463994, pdf: 0.0007089737523706667 },
// { x: 9.36412627831911, pdf: 0.0008284803923579783 },
// { x: 9.459816512273708, pdf: 0.0009655187182904854 },
// { x: 9.556484586616412, pdf: 0.001122187810647756 },
// { x: 9.65414049371306, pdf: 0.0013007588285175362 },
// { x: 9.752794328039583, pdf: 0.0015036764684296378 },
// { x: 9.852456287225452, pdf: 0.0017335581352873786 },
// { x: 9.953136673107782, pdf: 0.0019931904762988104 },
// { x: 10.054845892796212, pdf: 0.002285522927427827 },
// { x: 10.157594459748662, pdf: 0.002613657928409247 },
// { x: 10.261392994858094, pdf: 0.00298083747785083 },
// { x: 10.36625222755036, pdf: 0.00339042572532841 },
// { x: 10.472182996893284, pdf: 0.003845887333473609 },
// { x: 10.579196252717077, pdf: 0.0043507613904719255 },
// { x: 10.687303056746186, pdf: 0.004908630712509229 },
// { x: 10.796514583742733, pdf: 0.00552308644662074 },
// { x: 10.906842122661612, pdf: 0.006197687966875915 },
// { x: 11.018297077817413, pdf: 0.006935918150280943 },
// { x: 11.130890970063263, pdf: 0.007741134222211307 },
// { x: 11.2446354379817, pdf: 0.00861651447320171 },
// { x: 11.359542239087734, pdf: 0.009565001267702787 },
// { x: 11.475623251044201, pdf: 0.010589240888730601 },
// { x: 11.592890472889518, pdf: 0.011691520887560489 },
// { x: 11.711356026278011, pdf: 0.012873705731766286 },
// { x: 11.831032156732894, pdf: 0.014137171664688699 },
// { x: 11.951931234912063, pdf: 0.01548274180130405 },
// { x: 12.07406575788683, pdf: 0.016910622585775168 },
// { x: 12.197448350433708, pdf: 0.018420342820962683 },
// { x: 12.322091766339417, pdf: 0.020010696546175967 },
// { x: 12.448008889719205, pdf: 0.021679691082941988 },
// { x: 12.575212736348655, pdf: 0.023424501586361234 },
// { x: 12.703716455009102, pdf: 0.025241433428925014 },
// { x: 12.833533328846784, pdf: 0.027125893702261122 },
// { x: 12.964676776745897, pdf: 0.029072373048600202 },
// { x: 13.097160354715674, pdf: 0.03107443892702878 },
// { x: 13.230997757291643, pdf: 0.0331247412798984 },
// { x: 13.366202818951194, pdf: 0.03521503139309641 },
// { x: 13.50278951554363, pdf: 0.03733619454222775 },
// { x: 13.640771965734805, pdf: 0.039478296788055166 },
// { x: 13.780164432466549, pdf: 0.04163064603270107 },
// { x: 13.920981324430999, pdf: 0.04378186717793234 },
// { x: 14.063237197559985, pdf: 0.04591999094394063 },
// { x: 14.20694675652965, pdf: 0.048032555617702366 },
// { x: 14.35212485628044, pdf: 0.050106720711093324 },
// { x: 14.498786503552626, pdf: 0.052129391227648016 },
// { x: 14.646946858437516, pdf: 0.05408735097055588 },
// { x: 14.796621235944524, pdf: 0.05596740308048474 },
// { x: 14.947825107584242, pdf: 0.05775651577714975 },
// { x: 15.100574102967704, pdf: 0.05944197109973037 },
// { x: 15.254884011421979, pdf: 0.0610115143040895 },
// { x: 15.410770783622281, pdf: 0.06245350148414965 },
// { x: 15.568250533240755, pdf: 0.06375704294451334 },
// { x: 15.727339538612112, pdf: 0.06491213986400327 },
// { x: 15.888054244416281, pdf: 0.06590981185639877 },
// { x: 16.05041126337827, pdf: 0.06674221315497592 },
// { x: 16.21442737798537, pdf: 0.06740273531976387 },
// { x: 16.38011954222194, pdf: 0.06788609458751015 },
// { x: 16.547504883321892, pdf: 0.06818840224961567 },
// { x: 16.7166007035391, pdf: 0.06830721674690912 },
// { x: 16.8874244819359, pdf: 0.06824157650511187 },
// { x: 17.059993876189846, pdf: 0.06799201289332384 },
// { x: 17.234326724418974, pdf: 0.06756054306126427 },
// { x: 17.410441047025657, pdf: 0.06695064279031931 },
// { x: 17.58835504855935, pdf: 0.06616719986949657 },
// { x: 17.768087119598363, pdf: 0.06521644887107333 },
// { x: 17.949655838650838, pdf: 0.06410588854332999 },
// { x: 18.133079974075173, pdf: 0.06284418335117622 },
// { x: 18.318378486020073, pdf: 0.06144105097245895 },
// { x: 18.505570528384407, pdf: 0.05990713779209599 },
// { x: 18.69467545079712, pdf: 0.058253884622945194 },
// { x: 18.885712800617345, pdf: 0.056493385017886685 },
// { x: 19.078702324954982, pdf: 0.05463823861978922 },
// { x: 19.273663972711912, pdf: 0.05270140202414444 },
// { x: 19.470617896644058, pdf: 0.050696039603930654 },
// { x: 19.66958445544455, pdf: 0.04863537666985231 },
// { x: 19.870584215848147, pdf: 0.04653255721492421 },
// { x: 20.073637954757178, pdf: 0.04440050832501409 },
// { x: 20.278766661389206, pdf: 0.042251813131985824 },
// { x: 20.485991539446626, pdf: 0.04009859394984052 },
// { x: 20.69533400930847, pdf: 0.03795240697364387 },
// { x: 20.906815710244558, pdf: 0.03582414964330889 },
// { x: 21.120458502652312, pdf: 0.03372398148684345 },
// { x: 21.33628447031642, pdf: 0.03166125896774226 },
// { x: 21.554315922691586, pdf: 0.02964448457576937 },
// { x: 21.774575397208615, pdf: 0.02768127012591452 },
// { x: 21.997085661604032, pdf: 0.02577831397264268 },
// { x: 22.221869716273574, pdf: 0.023941391610736773 },
// { x: 22.448950796649655, pdf: 0.02217535892423078 },
// { x: 22.678352375603183, pdf: 0.020484167164369224 },
// { x: 22.910098165869883, pdf: 0.01887088858846632 },
// { x: 23.144212122501443, pdf: 0.017337751575253052 },
// { x: 23.380718445341685, pdf: 0.015886183949135855 },
// { x: 23.619641581528064, pdf: 0.014516863195202644 },
// { x: 23.861006228018695, pdf: 0.01322977222745922 },
// { x: 24.10483733414524, pdf: 0.01202425938261601 },
// { x: 24.35116010419185, pdf: 0.010899101348140865 },
// ... 1 more item
// ]
// }
arr = [13.8, 19.5, 16.7, 14.3, 17.5, 14.5, 12.6, 15.6, 8.9, 13.3, 17.1, 15, 16.3, 18.3, 18.7, 16.7, 20.9, 12.3, 22.3, 14.6, 20.1, 16.7, 16.8, 24.2, 21.2, 20.7, 18.6, 18.3, 15.9, 17.2, 18.8, 16.3, 20.5, 14.7, 17.5, 24.1, 14.6, 21.1, 17, 19.6, 21.2, 16, 16.5, 9.3, 16.2, 14.9, 16.3, 13.9, 18.4, 19.2, 24.6, 20.2, 12.8, 12.9, 14.1, 18.5, 13.4, 17.1, 9.9, 21.9, 19.6, 18.3, 19.7, 16.6, 21.7, 11.8, 15.9, 11.4, 14.3, 17.4, 16.4, 20.7, 18.6, 22, 17.9, 16.3, 15.4, 17.2, 17.3, 18.3, 16.8, 20.9, 15, 15.1, 18.6, 17.5, 14.7, 17.4, 13.8, 18.3, 17.2, 13.4, 12.5, 22.8, 18.6, 16.3, 16.1, 15.7, 20.8, 16.4]
r = await arrLogNormHist(arr, {
dx: 1,
})
console.log(r)
// => {
// avg: 17.048000000000002,
// std: 3.1686749612576244,
// avg_geo: 16.741131283482233,
// avg_log: 2.817868642436364,
// std_log: 0.19557811714294832,
// arr: [
// 13.8, 19.5, 16.7, 14.3, 17.5, 14.5, 12.6, 15.6, 8.9, 13.3,
// 17.1, 15, 16.3, 18.3, 18.7, 16.7, 20.9, 12.3, 22.3, 14.6,
// 20.1, 16.7, 16.8, 24.2, 21.2, 20.7, 18.6, 18.3, 15.9, 17.2,
// 18.8, 16.3, 20.5, 14.7, 17.5, 24.1, 14.6, 21.1, 17, 19.6,
// 21.2, 16, 16.5, 9.3, 16.2, 14.9, 16.3, 13.9, 18.4, 19.2,
// 24.6, 20.2, 12.8, 12.9, 14.1, 18.5, 13.4, 17.1, 9.9, 21.9,
// 19.6, 18.3, 19.7, 16.6, 21.7, 11.8, 15.9, 11.4, 14.3, 17.4,
// 16.4, 20.7, 18.6, 22, 17.9, 16.3, 15.4, 17.2, 17.3, 18.3,
// 16.8, 20.9, 15, 15.1, 18.6, 17.5, 14.7, 17.4, 13.8, 18.3,
// 17.2, 13.4, 12.5, 22.8, 18.6, 16.3, 16.1, 15.7, 20.8, 16.4
// ],
// min: 8,
// max: 25,
// barWidth: 1,
// ratioForCountToPdf: 0.01,
// bins: [
// { min: 8, max: 9, avg: 8.5, arr: [Array], counts: 1, pdf: 0.01 },
// { min: 9, max: 10, avg: 9.5, arr: [Array], counts: 2, pdf: 0.02 },
// { min: 10, max: 11, avg: 10.5, arr: [], counts: 0, pdf: 0 },
// { min: 11, max: 12, avg: 11.5, arr: [Array], counts: 2, pdf: 0.02 },
// { min: 12, max: 13, avg: 12.5, arr: [Array], counts: 5, pdf: 0.05 },
// { min: 13, max: 14, avg: 13.5, arr: [Array], counts: 6, pdf: 0.06 },
// {
// min: 14,
// max: 15,
// avg: 14.5,
// arr: [Array],
// counts: 11,
// pdf: 0.11
// },
// { min: 15, max: 16, avg: 15.5, arr: [Array], counts: 7, pdf: 0.07 },
// {
// min: 16,
// max: 17,
// avg: 16.5,
// arr: [Array],
// counts: 17,
// pdf: 0.17
// },
// {
// min: 17,
// max: 18,
// avg: 17.5,
// arr: [Array],
// counts: 12,
// pdf: 0.12
// },
// {
// min: 18,
// max: 19,
// avg: 18.5,
// arr: [Array],
// counts: 13,
// pdf: 0.13
// },
// { min: 19, max: 20, avg: 19.5, arr: [Array], counts: 5, pdf: 0.05 },
// { min: 20, max: 21, avg: 20.5, arr: [Array], counts: 8, pdf: 0.08 },
// { min: 21, max: 22, avg: 21.5, arr: [Array], counts: 6, pdf: 0.06 },
// { min: 22, max: 23, avg: 22.5, arr: [Array], counts: 2, pdf: 0.02 },
// { min: 23, max: 24, avg: 23.5, arr: [], counts: 0, pdf: 0 },
// { min: 24, max: 25, avg: 24.5, arr: [Array], counts: 3, pdf: 0.03 }
// ],
// curves: [
// { x: 8.9, pdf: 0.00037451241516612313 },
// { x: 8.990947415368343, pdf: 0.0004423975904714686 },
// { x: 9.082824205159403, pdf: 0.0005211775170478083 },
// { x: 9.17563986647449, pdf: 0.0006123292113229907 },
// { x: 9.269403993463994, pdf: 0.0007174814373991145 },
// { x: 9.36412627831911, pdf: 0.0008384221570662737 },
// { x: 9.459816512273708, pdf: 0.000977104942909971 },
// { x: 9.556484586616412, pdf: 0.0011356540643755286 },
// { x: 9.65414049371306, pdf: 0.0013163679344597463 },
// { x: 9.752794328039583, pdf: 0.001521720586050793 },
// { x: 9.852456287225452, pdf: 0.0017543608329108264 },
// { x: 9.953136673107782, pdf: 0.0020171087620143957 },
// { x: 10.054845892796212, pdf: 0.0023129492025569603 },
// { x: 10.157594459748662, pdf: 0.0026450218235501573 },
// { x: 10.261392994858094, pdf: 0.003016607527585039 },
// { x: 10.36625222755036, pdf: 0.00343111083403235 },
// { x: 10.472182996893284, pdf: 0.003892037981475291 },
// { x: 10.579196252717077, pdf: 0.0044029705271575875 },
// { x: 10.687303056746186, pdf: 0.004967534281059338 },
// { x: 10.796514583742733, pdf: 0.005589363483980187 },
// { x: 10.906842122661612, pdf: 0.006272060222478424 },
// { x: 11.018297077817413, pdf: 0.007019149168084312 },
// { x: 11.130890970063263, pdf: 0.00783402783287784 },
// { x: 11.2446354379817, pdf: 0.008719912646880127 },
// { x: 11.359542239087734, pdf: 0.009679781282915217 },
// { x: 11.475623251044201, pdf: 0.010716311779395365 },
// { x: 11.592890472889518, pdf: 0.01183181913821121 },
// { x: 11.711356026278011, pdf: 0.013028190200547476 },
// { x: 11.831032156732894, pdf: 0.014306817724664958 },
// { x: 11.951931234912063, pdf: 0.015668534702919693 },
// { x: 12.07406575788683, pdf: 0.017113550056804462 },
// { x: 12.197448350433708, pdf: 0.01864138693481423 },
// { x: 12.322091766339417, pdf: 0.020250824904730073 },
// { x: 12.448008889719205, pdf: 0.021939847375937287 },
// { x: 12.575212736348655, pdf: 0.02370559560539756 },
// { x: 12.703716455009102, pdf: 0.025544330630072103 },
// { x: 12.833533328846784, pdf: 0.027451404426688246 },
// { x: 12.964676776745897, pdf: 0.029421241525183394 },
// { x: 13.097160354715674, pdf: 0.03144733219415311 },
// { x: 13.230997757291643, pdf: 0.03352223817525717 },
// { x: 13.366202818951194, pdf: 0.03563761176981355 },
// { x: 13.50278951554363, pdf: 0.03778422887673447 },
// { x: 13.640771965734805, pdf: 0.03995203634951181 },
// { x: 13.780164432466549, pdf: 0.04213021378509347 },
// { x: 13.920981324430999, pdf: 0.04430724958406751 },
// { x: 14.063237197559985, pdf: 0.0464710308352679 },
// { x: 14.20694675652965, pdf: 0.04860894628511478 },
// { x: 14.35212485628044, pdf: 0.05070800135962642 },
// { x: 14.498786503552626, pdf: 0.052754943922379775 },
// { x: 14.646946858437516, pdf: 0.05473639918220253 },
// { x: 14.796621235944524, pdf: 0.056639011917450535 },
// { x: 14.947825107584242, pdf: 0.058449593966475526 },
// { x: 15.100574102967704, pdf: 0.06015527475292711 },
// { x: 15.254884011421979, pdf: 0.061743652475738556 },
// { x: 15.410770783622281, pdf: 0.06320294350195943 },
// { x: 15.568250533240755, pdf: 0.06452212745984748 },
// { x: 15.727339538612112, pdf: 0.06569108554237128 },
// { x: 15.888054244416281, pdf: 0.06670072959867554 },
// { x: 16.05041126337827, pdf: 0.0675431197128356 },
// { x: 16.21442737798537, pdf: 0.06821156814360102 },
// { x: 16.38011954222194, pdf: 0.06870072772256025 },
// { x: 16.547504883321892, pdf: 0.06900666307661103 },
// { x: 16.7166007035391, pdf: 0.06912690334787201 },
// { x: 16.8874244819359, pdf: 0.06906047542317319 },
// { x: 17.059993876189846, pdf: 0.0688079170480437 },
// { x: 17.234326724418974, pdf: 0.06837126957799942 },
// { x: 17.410441047025657, pdf: 0.06775405050380312 },
// { x: 17.58835504855935, pdf: 0.0669612062679305 },
// { x: 17.768087119598363, pdf: 0.06599904625752619 },
// { x: 17.949655838650838, pdf: 0.06487515920584992 },
// { x: 18.133079974075173, pdf: 0.06359831355139031 },
// { x: 18.318378486020073, pdf: 0.06217834358412844 },
// { x: 18.505570528384407, pdf: 0.06062602344560113 },
// { x: 18.69467545079712, pdf: 0.05895293123842051 },
// { x: 18.885712800617345, pdf: 0.05717130563810131 },
// { x: 19.078702324954982, pdf: 0.05529389748322667 },
// { x: 19.273663972711912, pdf: 0.053333818848434154 },
// { x: 19.470617896644058, pdf: 0.0513043920791778 },
// { x: 19.66958445544455, pdf: 0.04921900118989052 },
// { x: 19.870584215848147, pdf: 0.04709094790150329 },
// { x: 20.073637954757178, pdf: 0.044933314424914245 },
// { x: 20.278766661389206, pdf: 0.04275883488956964 },
// { x: 20.485991539446626, pdf: 0.040579777077238595 },
// { x: 20.69533400930847, pdf: 0.03840783585732758 },
// { x: 20.906815710244558, pdf: 0.036254039439028586 },
// { x: 21.120458502652312, pdf: 0.03412866926468555 },
// { x: 21.33628447031642, pdf: 0.032041194075355155 },
// { x: 21.554315922691586, pdf: 0.03000021839067859 },
// { x: 21.774575397208615, pdf: 0.028013445367425484 },
// { x: 21.997085661604032, pdf: 0.02608765374031438 },
// { x: 22.221869716273574, pdf: 0.024228688310065607 },
// { x: 22.448950796649655, pdf: 0.022441463231321544 },
// { x: 22.678352375603183, pdf: 0.020729977170341647 },
// { x: 22.910098165869883, pdf: 0.019097339251527908 },
// { x: 23.144212122501443, pdf: 0.01754580459415608 },
// { x: 23.380718445341685, pdf: 0.01607681815652548 },
// { x: 23.619641581528064, pdf: 0.01469106555354507 },
// { x: 23.861006228018695, pdf: 0.013388529494188726 },
// { x: 24.10483733414524, pdf: 0.012168550495207398 },
// { x: 24.35116010419185, pdf: 0.01102989056431855 },
// ... 1 more item
// ]
// }
arr = [12, 36, 9, 13, 6, 17, 7, 12, 31, 57, 44, 32, 16, 11, 10, 38, 31, 28, 26, 7, 16, 16, 16, 13, 7, 8, 12, 17, 11, 20, 7, 6, 14, 7, 37, 11, 7, 8, 8, 32, 29, 52, 20, 6, 11, 12, 33, 48, 10, 27, 11, 24, 17, 11, 23, 20, 13, 16, 16, 17, 13, 15, 13, 26, 11, 13, 29, 18, 18, 13, 11, 12, 9, 17, 19, 14, 19, 9, 37, 32, 14, 20, 13, 22, 12, 14, 33, 15, 20, 37, 24, 19, 15, 15, 5, 11, 13, 60, 39, 17, 6, 18, 40, 21, 18, 17, 12, 12, 10, 39, 27, 10, 8, 44, 36, 18, 11, 8, 13, 9, 25, 11, 10, 55, 54, 13, 8, 19, 38, 9, 17, 14, 9, 12, 54, 22, 11, 19, 50, 18, 12, 40, 52, 12, 15, 7, 12, 15, 18, 19, 11, 43, 23, 14, 25, 32, 23, 15, 12, 20, 14, 10, 12, 24, 50, 40, 16, 14, 9, 27, 9, 11, 17, 19, 12, 17, 14, 5, 24, 22, 60, 20, 9, 11, 11, 6, 7, 8, 31, 10, 12, 9, 11, 26, 14, 7, 14, 57, 19, 9, 10, 9, 19, 19, 15, 21, 48, 23, 26, 14, 46, 51, 10, 10, 9, 7, 19, 46, 27, 18, 12, 10, 36, 15, 5, 11, 13, 21, 15, 15, 16, 29, 44, 42, 7, 14, 9, 6, 22, 24, 18, 39, 7, 50, 33, 11, 20, 17, 18, 48, 8, 21, 20, 12, 41, 11, 18, 11, 58, 18, 21, 23, 12, 67, 35]
r = await arrLogNormHist(arr, {
n: 69,
min: 1,
max: 70,
})
// r.bins = r.bins.map((v) => {
// delete v.arr
// return v
// })
// fs.writeFileSync('bins.csv', w.getCsvStrFromData(r.bins), 'utf8')
// fs.writeFileSync('curves.csv', w.getCsvStrFromData(r.curves), 'utf8')
console.log(r)
// => {
// avg: 20.11320754716981,
// std: 13.078811770347688,
// avg_geo: 16.807250444562037,
// avg_log: 2.821810367388979,
// std_log: 0.5877705593811017,
// arr: [
// 12, 36, 9, 13, 6, 17, 7, 12, 31, 57, 44, 32,
// 16, 11, 10, 38, 31, 28, 26, 7, 16, 16, 16, 13,
// 7, 8, 12, 17, 11, 20, 7, 6, 14, 7, 37, 11,
// 7, 8, 8, 32, 29, 52, 20, 6, 11, 12, 33, 48,
// 10, 27, 11, 24, 17, 11, 23, 20, 13, 16, 16, 17,
// 13, 15, 13, 26, 11, 13, 29, 18, 18, 13, 11, 12,
// 9, 17, 19, 14, 19, 9, 37, 32, 14, 20, 13, 22,
// 12, 14, 33, 15, 20, 37, 24, 19, 15, 15, 5, 11,
// 13, 60, 39, 17,
// ... 165 more items
// ],
// min: 1,
// max: 70,
// barWidth: 1,
// ratioForCountToPdf: 0.0037735849056603774,
// bins: [
// { min: 1, max: 2, avg: 1.5, counts: 0, pdf: 0 },
// { min: 2, max: 3, avg: 2.5, counts: 0, pdf: 0 },
// { min: 3, max: 4, avg: 3.5, counts: 0, pdf: 0 },
// { min: 4, max: 5, avg: 4.5, counts: 3, pdf: 0.011320754716981131 },
// { min: 5, max: 6, avg: 5.5, counts: 6, pdf: 0.022641509433962263 },
// { min: 6, max: 7, avg: 6.5, counts: 12, pdf: 0.045283018867924525 },
// { min: 7, max: 8, avg: 7.5, counts: 8, pdf: 0.03018867924528302 },
// { min: 8, max: 9, avg: 8.5, counts: 14, pdf: 0.052830188679245285 },
// { min: 9, max: 10, avg: 9.5, counts: 11, pdf: 0.04150943396226415 },
// {
// min: 10,
// max: 11,
// avg: 10.5,
// counts: 21,
// pdf: 0.07924528301886792
// },
// {
// min: 11,
// max: 12,
// avg: 11.5,
// counts: 19,
// pdf: 0.07169811320754717
// },
// {
// min: 12,
// max: 13,
// avg: 12.5,
// counts: 12,
// pdf: 0.045283018867924525
// },
// {
// min: 13,
// max: 14,
// avg: 13.5,
// counts: 13,
// pdf: 0.04905660377358491
// },
// {
// min: 14,
// max: 15,
// avg: 14.5,
// counts: 11,
// pdf: 0.04150943396226415
// },
// {
// min: 15,
// max: 16,
// avg: 15.5,
// counts: 8,
// pdf: 0.03018867924528302
// },
// {
// min: 16,
// max: 17,
// avg: 16.5,
// counts: 11,
// pdf: 0.04150943396226415
// },
// {
// min: 17,
// max: 18,
// avg: 17.5,
// counts: 12,
// pdf: 0.045283018867924525
// },
// {
// min: 18,
// max: 19,
// avg: 18.5,
// counts: 11,
// pdf: 0.04150943396226415
// },
// {
// min: 19,
// max: 20,
// avg: 19.5,
// counts: 9,
// pdf: 0.033962264150943396
// },
// {
// min: 20,
// max: 21,
// avg: 20.5,
// counts: 5,
// pdf: 0.018867924528301886
// },
// {
// min: 21,
// max: 22,
// avg: 21.5,
// counts: 4,
// pdf: 0.01509433962264151
// },
// {
// min: 22,
// max: 23,
// avg: 22.5,
// counts: 5,
// pdf: 0.018867924528301886
// },
// {
// min: 23,
// max: 24,
// avg: 23.5,
// counts: 5,
// pdf: 0.018867924528301886
// },
// {
// min: 24,
// max: 25,
// avg: 24.5,
// counts: 2,
// pdf: 0.007547169811320755
// },
// {
// min: 25,
// max: 26,
// avg: 25.5,
// counts: 4,
// pdf: 0.01509433962264151
// },
// {
// min: 26,
// max: 27,
// avg: 26.5,
// counts: 4,
// pdf: 0.01509433962264151
// },
// {
// min: 27,
// max: 28,
// avg: 27.5,
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 28,
// max: 29,
// avg: 28.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// { min: 29, max: 30, avg: 29.5, counts: 0, pdf: 0 },
// {
// min: 30,
// max: 31,
// avg: 30.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 31,
// max: 32,
// avg: 31.5,
// counts: 4,
// pdf: 0.01509433962264151
// },
// {
// min: 32,
// max: 33,
// avg: 32.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// { min: 33, max: 34, avg: 33.5, counts: 0, pdf: 0 },
// {
// min: 34,
// max: 35,
// avg: 34.5,
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 35,
// max: 36,
// avg: 35.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 36,
// max: 37,
// avg: 36.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 37,
// max: 38,
// avg: 37.5,
// counts: 2,
// pdf: 0.007547169811320755
// },
// {
// min: 38,
// max: 39,
// avg: 38.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 39,
// max: 40,
// avg: 39.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 40,
// max: 41,
// avg: 40.5,
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 41,
// max: 42,
// avg: 41.5,
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 42,
// max: 43,
// avg: 42.5,
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 43,
// max: 44,
// avg: 43.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// { min: 44, max: 45, avg: 44.5, counts: 0, pdf: 0 },
// {
// min: 45,
// max: 46,
// avg: 45.5,
// counts: 2,
// pdf: 0.007547169811320755
// },
// { min: 46, max: 47, avg: 46.5, counts: 0, pdf: 0 },
// {
// min: 47,
// max: 48,
// avg: 47.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// { min: 48, max: 49, avg: 48.5, counts: 0, pdf: 0 },
// {
// min: 49,
// max: 50,
// avg: 49.5,
// counts: 3,
// pdf: 0.011320754716981131
// },
// {
// min: 50,
// max: 51,
// avg: 50.5,
// counts: 1,
// pdf: 0.0037735849056603774
// },
// {
// min: 51,
// max: 52,
// avg: 51.5,
// counts: 2,
// pdf: 0.007547169811320755
// },
// { min: 52, max: 53, avg: 52.5, counts: 0, pdf: 0 },
// {
// min: 53,
// max: 54,
// avg: 53.5,
// counts: 2,
// pdf: 0.007547169811320755
// },
// {
// min: 54,
// max: 55,
// avg: 54.5,
// counts: 1,
// pdf: 0.0037735849056603774
// },
// { min: 55, max: 56, avg: 55.5, counts: 0, pdf: 0 },
// {
// min: 56,
// max: 57,
// avg: 56.5,
// counts: 2,
// pdf: 0.007547169811320755
// },
// {
// min: 57,
// max: 58,
// avg: 57.5,
// counts: 1,
// pdf: 0.0037735849056603774
// },
// { min: 58, max: 59, avg: 58.5, counts: 0, pdf: 0 },
// {
// min: 59,
// max: 60,
// avg: 59.5,
// counts: 2,
// pdf: 0.007547169811320755
// },
// { min: 60, max: 61, avg: 60.5, counts: 0, pdf: 0 },
// { min: 61, max: 62, avg: 61.5, counts: 0, pdf: 0 },
// { min: 62, max: 63, avg: 62.5, counts: 0, pdf: 0 },
// { min: 63, max: 64, avg: 63.5, counts: 0, pdf: 0 },
// { min: 64, max: 65, avg: 64.5, counts: 0, pdf: 0 },
// { min: 65, max: 66, avg: 65.5, counts: 0, pdf: 0 },
// {
// min: 66,
// max: 67,
// avg: 66.5,
// counts: 1,
// pdf: 0.0037735849056603774
// },
// { min: 67, max: 68, avg: 67.5, counts: 0, pdf: 0 },
// { min: 68, max: 69, avg: 68.5, counts: 0, pdf: 0 },
// { min: 69, max: 70, avg: 69.5, counts: 0, pdf: 0 }
// ],
// curves: [
// { x: 5, pdf: 0.006970263647771901 },
// { x: 5.1314612337167205, pdf: 0.007627449421952031 },
// { x: 5.266378878627506, pdf: 0.008330340805749705 },
// { x: 5.404843811548318, pdf: 0.00908028550685169 },
// { x: 5.546949298650784, pdf: 0.009878466707792261 },
// { x: 5.6927910582837296, pdf: 0.010725878642582927 },
// { x: 5.84246732544643, pdf: 0.011623301921523003 },
// { x: 5.996078917956994, pdf: 0.012571278882578144 },
// { x: 6.153729304360484, pdf: 0.013570089271484143 },
// { x: 6.315524673622478, pdf: 0.014619726573641327 },
// { x: 6.481574006655039, pdf: 0.015719875338288225 },
// { x: 6.65198914972326, pdf: 0.016869889848776513 },
// { x: 6.826884889781832, pdf: 0.018068774501442092 },
// { x: 7.006379031792385, pdf: 0.01931516625905629 },
// { x: 7.190592478073664, pdf: 0.020607319542689222 },
// { x: 7.379649309738012, pdf: 0.021943093917644478 },
// { x: 7.573676870268995, pdf: 0.02331994491464581 },
// { x: 7.772805851296467, pdf: 0.024734918306493096 },
// { x: 7.9771703806268635, pdf: 0.026184648132895973 },
// { x: 8.186908112588002, pdf: 0.0276653587322046 },
// { x: 8.402160320749253, pdf: 0.029172870998490696 },
// { x: 8.62307199307953, pdf: 0.030702613036224635 },
// { x: 8.849791929607198, pdf: 0.032249635333126726 },
// { x: 9.082472842647686, pdf: 0.03380863051525675 },
// { x: 9.321271459666303, pdf: 0.03537395768779317 },
// { x: 9.566348628845542, pdf: 0.036939671301112156 },
// { x: 9.817869427428002, pdf: 0.03849955441568438 },
// { x: 10.076003272907876, pdf: 0.040047156172040195 },
// { x: 10.340924037145914, pdf: 0.04157583320475795 },
// { x: 10.612810163484735, pdf: 0.04307879467330953 },
// { x: 10.891844786943345, pdf: 0.04454915051888296 },
// { x: 11.178215857571868, pdf: 0.04597996249623112 },
// { x: 11.472116267049511, pdf: 0.047364297474381256 },
// { x: 11.773743978611112, pdf: 0.04869528245084682 },
// { x: 12.083302160389717, pdf: 0.049966160681897076 },
// { x: 12.400999322265069, pdf: 0.05117034829744484 },
// { x: 12.727049456310107, pdf: 0.052301490744063775 },
// { x: 13.061672180930158, pdf: 0.05335351838424792 },
// { x: 13.405092888791849, pdf: 0.05432070057481254 },
// { x: 13.757542898641415, pdf: 0.05519769755265327 },
// { x: 14.119259611114638, pdf: 0.05597960947208052 },
// { x: 14.490486668643399, pdf: 0.05666202196456824 },
// { x: 14.87147411956651, pdf: 0.05724104762873568 },
// { x: 15.262478586555412, pdf: 0.057713362905240304 },
// { x: 15.663763439468136, pdf: 0.05807623984732463 },
// { x: 16.075598972748008, pdf: 0.05832757236216284 },
// { x: 16.498262587486547, pdf: 0.058465896569855 },
// { x: 16.93203897827323, pdf: 0.058490405004725236 },
// { x: 17.37722032495791, pdf: 0.05840095446617321 },
// { x: 17.834106489455163, pdf: 0.05819806741228262 },
// { x: 18.303005217722994, pdf: 0.05788292687721193 },
// { x: 18.784232347052086, pdf: 0.05745736498154505 },
// { x: 19.27811201880509, pdf: 0.05692384519172349 },
// { x: 19.784976896749342, pdf: 0.05628543856889881 },
// { x: 20.30516839113004, pdf: 0.055545794327578314 },
// { x: 20.839036888634787, pdf: 0.05470910509891854 },
// { x: 21.386941988404423, pdf: 0.05378006736119961 },
// { x: 21.949252744249144, pdf: 0.05276383755977885 },
// { x: 22.526347913232968, pdf: 0.05166598448973478 },
// { x: 23.11861621079411, pdf: 0.050492438555709084 },
// { x: 23.726456572572985, pdf: 0.04924943855457474 },
// { x: 24.350278423124315, pdf: 0.04794347664714489 },
// { x: 24.99050195169423, pdf: 0.0465812421950407 },
// { x: 25.647558395248204, pdf: 0.04516956513812022 },
// { x: 26.3218903289404, pdf: 0.04371535957679493 },
// { x: 27.013951964220148, pdf: 0.042225568202584655 },
// { x: 27.724209454776272, pdf: 0.04070710819001564 },
// { x: 28.45314121052541, pdf: 0.039166819124245834 },
// { x: 29.20123821985576, pdf: 0.03761141349253633 },
// { x: 29.96900438034338, pdf: 0.036047430214923175 },
// { x: 30.756956838163735, pdf: 0.03448119163131486 },
// { x: 31.565626336427126, pdf: 0.032918764299941956 },
// { x: 32.39555757267267, pdf: 0.0313659238968475 },
// { x: 33.2473095657616, pdf: 0.029828124439166825 },
// { x: 34.12145603241695, pdf: 0.028310471987520833 },
// { x: 35.01858577366343, pdf: 0.026817702916113594 },
// { x: 35.93930307142755, pdf: 0.025354166774189748 },
// { x: 36.884228095565355, pdf: 0.023923813700393242 },
// { x: 37.853997321591756, pdf: 0.022530186293193852 },
// { x: 38.849263959392935, pdf: 0.021176415786713233 },
// { x: 39.8706983932106, pdf: 0.019865222332660623 },
// { x: 40.91898863319436, pdf: 0.01859891914621804 },
// { x: 41.9948407788264, pdf: 0.01737942023699428 },
// { x: 43.09897949453077, pdf: 0.016208251415856353 },
// { x: 44.2321484977873, pdf: 0.015086564244669668 },
// { x: 45.39511106007937, pdf: 0.014015152578726816 },
// { x: 46.5886505210125, pdf: 0.012994471340790056 },
// { x: 47.813570815950385, pdf: 0.01202465716097319 },
// { x: 49.07069701752372, pdf: 0.011105550517804371 },
// { x: 50.36087589137634, pdf: 0.010236719022315948 },
// { x: 51.684976466523345, pdf: 0.009417481498404745 },
// { x: 53.04389062070511, pdf: 0.008646932528443427 },
// { x: 54.43853368113166, pdf: 0.007923967152609103 },
// { x: 55.86984504102183, pdf: 0.007247305433011932 },
// { x: 57.33878879235279, pdf: 0.006615516618826953 },
// { x: 58.846354375245824, pdf: 0.00602704267563308 },
// { x: 60.39355724442606, pdf: 0.005480220970436274 },
// { x: 61.9814395532048, pdf: 0.0049733059328185055 },
// { x: 63.61107085544534, pdf: 0.004504489541766293 },
// { x: 65.28354882598506, pdf: 0.004071920516492762 },
// ... 1 more item
// ]
// }
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Attributes | Default | Description | ||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
||||||||||||||||||||||||||||||||
opt |
Object |
<optional> |
{}
|
輸入設定物件，預設{} Properties
|
Returns:
回傳反函數值
- Type
- Number
(async, static) arrLogNormInv(arr, ratio) → {Number}
- Description:
基於對數常態累加分布計算指定位置之反函數值，會先計算陣列內有效數字取對數(log)後之平均值和標準差，並基於其為常態累加分布，計算指定位置之反函數值後，再取指數(exp)值
Unit Test: Github
- Source:
Example
async function test() {
let arr
let r
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
r = await arrLogNormInv(arr, 0.25)
console.log(r.inv)
// => 16.096845206281877
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
r = await arrLogNormInv(arr, 0.5)
console.log(r.inv)
// => 27.201738017491444
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
r = await arrLogNormInv(arr, 0.75)
console.log(r.inv)
// => 45.96767513695641
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
r = await arrLogNormInv(arr, 0.5)
console.log(r.inv)
// => 1.0499093195835956
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
r = await arrLogNormInv(arr, 0.5)
console.log(r.inv)
// => 1.0499093195835956
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
ratio |
Number | 輸入指定位置浮點數，需介於0至1之間 |
Returns:
回傳反函數取指數(exp)值
- Type
- Number
(static) arrMovingAverage(arr, optopt) → {Array}
- Description:
計算陣列內有效數字之移動平均值
Unit Test: Github
- Source:
Example
let arr
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrMovingAverage(arr))
// => [
// -2.5, -2,
// -1.75, -1.42,
// -0.9399999999999998, -0.44000000000000006,
// -0.24000000000000005, -0.02,
// 0.02, 0.24,
// 0.44000000000000006, 0.9400000000000001,
// 1.42, 5.9,
// 7.125, 9.166666666666666,
// 12.5
// ]
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrMovingAverage(arr, { selectCountHalf: 1 }))
// => [
// 0,
// 0,
// 0.03333333333333333,
// 0.06666666666666667,
// 0.39999999999999997,
// 0.7000000000000001,
// 1.5,
// 2,
// 9.166666666666666,
// 12.5,
// 22.5
// ]Parameters:
| Name | Type | Attributes | Default | Description | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
||||||||||||
opt |
Object |
<optional> |
{}
|
輸入設定物件，預設{} Properties
|
Returns:
回傳移動平均值陣列
- Type
- Array
(async, static) arrNormHist(arr, optopt) → {Number}
- Description:
基於常態分布計算陣列數據分組直方圖、統計與趨勢線數據
Unit Test: Github
- Source:
Example
async function test() {
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Attributes | Default | Description | ||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
||||||||||||||||||||||||||||||||
opt |
Object |
<optional> |
{}
|
輸入設定物件，預設{} Properties
|
Returns:
回傳反函數值
- Type
- Number
(async, static) arrNormInv(arr, ratio) → {Number}
- Description:
基於常態累加分布計算指定位置之反函數值
Unit Test: Github
- Source:
Example
async function test() {
let arr
let r
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
r = await arrNormInv(arr, 0.25)
console.log(r.inv)
// => 22.47539788913989
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
r = await arrNormInv(arr, 0.5)
console.log(r.inv)
// => 33.18181818181818
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
r = await arrNormInv(arr, 0.75)
console.log(r.inv)
// => 43.88823847449647
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
r = await arrNormInv(arr, 0.5)
console.log(r.inv)
// => 1.4999999999999996
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
r = await arrNormInv(arr, 0.5)
console.log(r.inv)
// => 3.2999999999999994
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
ratio |
Number | 輸入指定位置浮點數，需介於0至1之間 |
Returns:
回傳反函數值
- Type
- Number
(static) arrQuartile(arr, ratio) → {Number}
- Description:
計算陣列內有效數字之分位數值
Unit Test: Github
- Source:
Example
let arr
arr = [3, 6, 7, 8, 8, 10, 13, 15, 16, 20]
console.log(arrQuartile(arr, 0.25))
// => 7
arr = [3, 6, 7, 8, 8, 10, 13, 15, 16, 20]
console.log(arrQuartile(arr, 0.5))
// => 9
arr = [3, 6, 7, 8, 8, 10, 13, 15, 16, 20]
console.log(arrQuartile(arr, 0.75))
// => 15
arr = [1, 2, 3, 4, 5, 6]
console.log(arrQuartile(arr, 0.25))
// => 2
arr = [3, 6, 7, 8, 8, 9, 10, 13, 15, 16, 20]
console.log(arrQuartile(arr, 0.5))
// => 9
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(arrQuartile(arr, 0.25))
// => 15
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(arrQuartile(arr, 0.5))
// => 40
arr = [6, 47, 49, 15, 42, 41, 7, 39, 43, 40, 36]
console.log(arrQuartile(arr, 0.75))
// => 43
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrQuartile(arr, 0.5))
// => 0
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrQuartile(arr, 0.5))
// => 1Parameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
ratio |
Number | 輸入指定位置浮點數，需介於0至1之間 |
Returns:
回傳分位數值
- Type
- Number
(static) arrStd(arr) → {Number}
- Description:
計算陣列內有效數字之標準差
Unit Test: Github
- Source:
Example
let arr
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrStd(arr))
// => 5.985339231345682
arr = ['abc', '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(arrStd(arr))
// => 7.269456650947167
arr = [55, 68, 45, 78, 150, 241, 162, 156, 182, 125, 75, 89, 91, 95, 92, 65, 75, 85, 95, 105, 132, 120, 142, 110, 111, 130, 128, 130, 108, 109]
console.log(arrStd(arr))
// => 40.847473507599254, 為除以29(n-1)的stdParameters:
| Name | Type | Description |
|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
Returns:
回傳標準差
- Type
- Number
(static) bin(arr, nopt, optopt) → {Object}
Example
let arr
arr = ['abc', '-2.5', -2.5, '-1', -1, '-0.1', -0.1, '0', 0, '0.1', 0.1, '1', 1, '2.5', 2.5, 22.5, 'xyz']
console.log(bin(arr, 4))
// => [
// {
// min: -2.5,
// max: 3.75,
// avg: 0.625,
// arr: [
// -2.5, -2.5, -1, -1,
// -0.1, -0.1, 0, 0,
// 0.1, 0.1, 1, 1,
// 2.5, 2.5
// ]
// },
// { min: 3.75, max: 10, avg: 6.875, arr: [] },
// { min: 10, max: 16.25, avg: 13.125, arr: [] },
// { min: 16.25, max: 22.5, avg: 19.375, arr: [ 22.5 ] }
// ]
arr = [1.1, 2.2, 3.3, 4.4, 5.5, 6.6]
console.log(bin(arr, 3))
// => [
// {
// min: 1.1,
// max: 2.9333333333333336,
// avg: 2.0166666666666666,
// arr: [ 1.1, 2.2 ]
// },
// {
// min: 2.9333333333333336,
// max: 4.766666666666667,
// avg: 3.85,
// arr: [ 3.3, 4.4 ]
// },
// {
// min: 4.766666666666667,
// max: 6.6,
// avg: 5.683333333333334,
// arr: [ 5.5, 6.6 ]
// }
// ]
arr = [1.1, 2.2, 3.3, 4.4, 5.5, 6.6]
console.log(bin(arr, 5))
// => [
// { min: 1.1, max: 2.2, avg: 1.6500000000000001, arr: [ 1.1, 2.2 ] },
// { min: 2.2, max: 3.3000000000000003, avg: 2.75, arr: [ 3.3 ] },
// {
// min: 3.3000000000000003,
// max: 4.4,
// avg: 3.8500000000000005,
// arr: [ 4.4 ]
// },
// { min: 4.4, max: 5.5, avg: 4.95, arr: [ 5.5 ] },
// { min: 5.5, max: 6.6, avg: 6.05, arr: [ 6.6 ] }
// ]
arr = [1.1, 2.2, 3.3, 4.4, 5.5, 6.6]
console.log(bin(arr, 5, { min: 0, max: 10 }))
// => [
// { min: 0, max: 2, avg: 1, arr: [ 1.1 ] },
// { min: 2, max: 4, avg: 3, arr: [ 2.2, 3.3 ] },
// { min: 4, max: 6, avg: 5, arr: [ 4.4, 5.5 ] },
// { min: 6, max: 8, avg: 7, arr: [ 6.6 ] },
// { min: 8, max: 10, avg: 9, arr: [] }
// ]Parameters:
| Name | Type | Attributes | Default | Description | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
|||||||||||||||||
n |
Integer |
<optional> |
30
|
輸入分組數量整數，預設30 |
|||||||||||||||
opt |
Object |
<optional> |
{}
|
輸入設定物件，預設{} Properties
|
Returns:
回傳數據分組資訊物件
- Type
- Object
(async, static) histGen(arr, fun, optopt) → {Promise}
- Description:
數據陣列進行直方圖分組，並基於外部提供函數產生擬合數據
Unit Test: Github
- Source:
Example
async function test() {
let arr
let opt
let r
arr = [13.8, 19.5, 16.7, 14.3, 17.5, 14.5, 12.6, 15.6, 8.9, 13.3, 17.1, 15, 16.3, 18.3, 18.7, 16.7, 20.9, 12.3, 22.3, 14.6, 20.1, 16.7, 16.8, 24.2, 21.2, 20.7, 18.6, 18.3, 15.9, 17.2, 18.8, 16.3, 20.5, 14.7, 17.5, 24.1, 14.6, 21.1, 17, 19.6, 21.2, 16, 16.5, 9.3, 16.2, 14.9, 16.3, 13.9, 18.4, 19.2, 24.6, 20.2, 12.8, 12.9, 14.1, 18.5, 13.4, 17.1, 9.9, 21.9, 19.6, 18.3, 19.7, 16.6, 21.7, 11.8, 15.9, 11.4, 14.3, 17.4, 16.4, 20.7, 18.6, 22, 17.9, 16.3, 15.4, 17.2, 17.3, 18.3, 16.8, 20.9, 15, 15.1, 18.6, 17.5, 14.7, 17.4, 13.8, 18.3, 17.2, 13.4, 12.5, 22.8, 18.6, 16.3, 16.1, 15.7, 20.8, 16.4]
opt = {
n: 10,
min: 12,
max: 23,
}
r = await histGen(arr, (params) => {
// console.log('params', params)
let avg = arrAverage(params.arr)
let std = arrStd(params.arr)
let ry = (std * Math.sqrt(2 * Math.PI))
let curveY = params.curveX.map((x) => {
let y = 0
if (ry !== 0) {
y = 1 / ry * Math.exp(-((x - avg) ** 2) / (2 * std ** 2))
}
return y
})
return curveY
}, opt)
// let c = ''
// r.curveX.forEach((v, k) => {
// let x = r.curveX[k]
// let y = r.curveY[k]
// c += `${x}, ${y}\n`
// })
// console.log(c)
console.log(r)
// => {
// arr: [
// 13.8, 19.5, 16.7, 14.3, 17.5, 14.5, 12.6, 15.6, 8.9, 13.3,
// 17.1, 15, 16.3, 18.3, 18.7, 16.7, 20.9, 12.3, 22.3, 14.6,
// 20.1, 16.7, 16.8, 24.2, 21.2, 20.7, 18.6, 18.3, 15.9, 17.2,
// 18.8, 16.3, 20.5, 14.7, 17.5, 24.1, 14.6, 21.1, 17, 19.6,
// 21.2, 16, 16.5, 9.3, 16.2, 14.9, 16.3, 13.9, 18.4, 19.2,
// 24.6, 20.2, 12.8, 12.9, 14.1, 18.5, 13.4, 17.1, 9.9, 21.9,
// 19.6, 18.3, 19.7, 16.6, 21.7, 11.8, 15.9, 11.4, 14.3, 17.4,
// 16.4, 20.7, 18.6, 22, 17.9, 16.3, 15.4, 17.2, 17.3, 18.3,
// 16.8, 20.9, 15, 15.1, 18.6, 17.5, 14.7, 17.4, 13.8, 18.3,
// 17.2, 13.4, 12.5, 22.8, 18.6, 16.3, 16.1, 15.7, 20.8, 16.4
// ],
// min: 12,
// max: 23.000000000000007,
// barWidth: 1.0999999999999996,
// bins: [
// { min: 12, max: 13.1, avg: 12.55, arr: [Array], counts: 5 },
// {
// min: 13.1,
// max: 14.2,
// avg: 13.649999999999999,
// arr: [Array],
// counts: 7
// },
// {
// min: 14.2,
// max: 15.299999999999999,
// avg: 14.75,
// arr: [Array],
// counts: 11
// },
// {
// min: 15.299999999999999,
// max: 16.4,
// avg: 15.849999999999998,
// arr: [Array],
// counts: 15
// },
// { min: 16.4, max: 17.5, avg: 16.95, arr: [Array], counts: 19 },
// { min: 17.5, max: 18.6, avg: 18.05, arr: [Array], counts: 12 },
// {
// min: 18.6,
// max: 19.700000000000003,
// avg: 19.150000000000002,
// arr: [Array],
// counts: 7
// },
// {
// min: 19.700000000000003,
// max: 20.800000000000004,
// avg: 20.250000000000004,
// arr: [Array],
// counts: 6
// },
// {
// min: 20.800000000000004,
// max: 21.900000000000006,
// avg: 21.350000000000005,
// arr: [Array],
// counts: 7
// },
// {
// min: 21.900000000000006,
// max: 23.000000000000007,
// avg: 22.450000000000006,
// arr: [Array],
// counts: 3
// }
// ],
// counts: [
// 5, 7, 11, 15, 19,
// 12, 7, 6, 7, 3
// ],
// pdfs: [
// 0.04940711462450595,
// 0.06916996047430833,
// 0.10869565217391308,
// 0.14822134387351785,
// 0.1877470355731226,
// 0.11857707509881428,
// 0.06916996047430833,
// 0.05928853754940714,
// 0.06916996047430833,
// 0.02964426877470357
// ],
// ratioForCountToPdf: 0.00988142292490119,
// curveX: [
// 12, 12.11, 12.219999999999999,
// 12.329999999999998, 12.439999999999998, 12.549999999999997,
// 12.659999999999997, 12.769999999999996, 12.879999999999995,
// 12.989999999999995, 13.099999999999994, 13.209999999999994,
// 13.319999999999993, 13.429999999999993, 13.539999999999992,
// 13.649999999999991, 13.759999999999991, 13.86999999999999,
// 13.97999999999999, 14.08999999999999, 14.199999999999989,
// 14.309999999999988, 14.419999999999987, 14.529999999999987,
// 14.639999999999986, 14.749999999999986, 14.859999999999985,
// 14.969999999999985, 15.079999999999984, 15.189999999999984,
// 15.299999999999983, 15.409999999999982, 15.519999999999982,
// 15.629999999999981, 15.73999999999998, 15.84999999999998,
// 15.95999999999998, 16.06999999999998, 16.17999999999998,
// 16.289999999999978, 16.399999999999977, 16.509999999999977,
// 16.619999999999976, 16.729999999999976, 16.839999999999975,
// 16.949999999999974, 17.059999999999974, 17.169999999999973,
// 17.279999999999973, 17.389999999999972, 17.49999999999997,
// 17.60999999999997, 17.71999999999997, 17.82999999999997,
// 17.93999999999997, 18.04999999999997, 18.159999999999968,
// 18.269999999999968, 18.379999999999967, 18.489999999999966,
// 18.599999999999966, 18.709999999999965, 18.819999999999965,
// 18.929999999999964, 19.039999999999964, 19.149999999999963,
// 19.259999999999962, 19.369999999999962, 19.47999999999996,
// 19.58999999999996, 19.69999999999996, 19.80999999999996,
// 19.91999999999996, 20.02999999999996, 20.139999999999958,
// 20.249999999999957, 20.359999999999957, 20.469999999999956,
// 20.579999999999956, 20.689999999999955, 20.799999999999955,
// 20.909999999999954, 21.019999999999953, 21.129999999999953,
// 21.239999999999952, 21.34999999999995, 21.45999999999995,
// 21.56999999999995, 21.67999999999995, 21.78999999999995,
// 21.89999999999995, 22.00999999999995, 22.119999999999948,
// 22.229999999999947, 22.339999999999947, 22.449999999999946,
// 22.559999999999945, 22.669999999999945, 22.779999999999944,
// 22.889999999999944,
// ... 1 more item
// ],
// curveY: [
// 0.03539347632001737, 0.037383482855803, 0.039437822053457874,
// 0.04155494476232438, 0.043732984782065484, 0.04596975107654172,
// 0.04826272158141871, 0.05060903873486474, 0.053005506852505095,
// 0.05544859145799284, 0.057934420669161386, 0.06045878872679094,
// 0.06301716173861893, 0.06560468569544393, 0.06821619679912554,
// 0.07084623412410286, 0.07348905461489254, 0.07613865040205554,
// 0.07878876839852786, 0.08143293211719617, 0.08406446562938243,
// 0.08667651956270586, 0.0892620990158537, 0.09181409324734967,
// 0.09432530697570551, 0.09678849310961433, 0.09919638670933023,
// 0.10154173996430707, 0.10381735795775265, 0.10601613497619995,
// 0.10813109111168648, 0.11015540889583084, 0.11208246969914742,
// 0.11390588962545672, 0.11561955463032393, 0.11721765459414842,
// 0.11869471608486172, 0.120045633552169, 0.12126569870485275,
// 0.12235062783478269, 0.12329658686584205, 0.12410021392285919,
// 0.124758639234666, 0.12526950220640412, 0.1256309655189545,
// 0.12584172613764152, 0.1259010231379035, 0.12580864228215807,
// 0.12556491730933672, 0.12517072792622605, 0.12462749451753433,
// 0.12393716961919929, 0.1231022262265693, 0.12212564303543284,
// 0.1210108867391587, 0.11976189152917438, 0.11838303596840025,
// 0.11687911742784585, 0.11525532429515117, 0.11351720618024314,
// 0.11167064235732105, 0.10972180869396257, 0.10767714332716188,
// 0.10554331135251384, 0.10332716879651553, 0.1010357261430725,
// 0.09867611168380674, 0.09625553495773567, 0.09378125053941684,
// 0.0912605224258574, 0.08870058926151618, 0.0861086306277478,
// 0.08349173460824426, 0.08085686682562278, 0.07821084112651096,
// 0.0755602920735203, 0.07291164938261302, 0.07027111442379702,
// 0.06764463888206981, 0.06503790565431186, 0.06245631203663879,
// 0.05990495523578081, 0.057388620217582655, 0.054911769885907534,
// 0.05247853756626619, 0.050092721750548005, 0.04775778304244922,
// 0.045476843227705024, 0.04325268637914335, 0.04108776189397607,
// 0.03898418934969129, 0.03694376505545445, 0.03496797016808652,
// 0.03305798023546953, 0.031214676025614625, 0.029438655496583702,
// 0.027730246760929483, 0.026089521898245954, 0.02451631147072182,
// 0.023010219599172477,
// ... 1 more item
// ]
// }
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Attributes | Default | Description | ||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
||||||||||||||||||||||||||||||||
fun |
function | 輸入產生擬合函數 |
||||||||||||||||||||||||||||||||
opt |
Object |
<optional> |
{}
|
輸入設定物件，預設{} Properties
|
Returns:
回傳Promise，若成功則resolve數據分組與統計數據物件，若失敗則reject錯誤訊息
- Type
- Promise
(static) regLine(arr, optopt) → {Object|Promise}
- Description:
針對數據進行線性回歸(y=mx+b)
Unit Test: Github
- Source:
Example
async function test() {
let arr
let r
arr = [
[1, 2.5],
[2.5, 1.1],
[4, 0.5],
]
r = await regLine(arr)
console.log(r)
// => { m: -0.6666666666666664, b: 3.0333333333333323 }
arr = [
[1, 0.5],
[2.5, 1.1],
[4, 2.5],
]
r = await regLine(arr)
console.log(r)
// => { m: 0.666666666666667, b: -0.3000000000000007 }
arr = [
[1, 0.5],
[2.5, 1.1],
[4, 2.5],
]
r = await regLine(arr, { useRegIntercept: false }) //不使用截距, 也就是截距=0
console.log(r)
// => { m: 0.5698924731182796, b: 0 }
arr = [
[1, 2.5],
[2.5, 1.1],
[4, 0.5],
]
r = await regLine(arr, { interpX: 2 })
console.log(r)
// => {
// m: -0.6666666666666664,
// b: 3.0333333333333323,
// interpY: 1.6999999999999995
// }
arr = [
[1, 2.5],
[2.5, 1.1],
[4, 0.5],
]
r = regLine(arr, { useSync: true }) //使用同步函數(sync)
console.log(r)
// => { m: -0.6666666666666664, b: 3.0333333333333323 }
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Attributes | Default | Description | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
||||||||||||||||||||||
opt |
Object |
<optional> |
{}
|
輸入設定物件，預設{} Properties
|
Returns:
若useSync=true回傳回歸結果物件，若useSync=false則回傳Promise，此時若成功則resolve回歸結果物件，若失敗則reject錯誤訊息
- Type
- Object | Promise
(static) regPower(arr, optopt) → {Object|Promise}
- Description:
針對數據進行乘冪(Power)回歸(y=ax^b)
Unit Test: Github
- Source:
Example
async function test() {
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Attributes | Default | Description | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arr |
Array | 輸入陣列，只提取有效數字(或為字串的數字)進行計算 |
|||||||||||||||||
opt |
Object |
<optional> |
{}
|
輸入設定物件，預設{} Properties
|
Returns:
若useSync=true回傳回歸結果物件，若useSync=false則回傳Promise，此時若成功則resolve回歸結果物件，若失敗則reject錯誤訊息
- Type
- Object | Promise
(async, static) sampleRandom(name, optopt) → {Number|Array}
- Description:
依照指定統計分布隨機產生值或陣列
Unit Test: Github
- Source:
Example
async function test() {
let r
r = await sampleRandom('normal', { mu: 100, sigma: 50 })
console.log(r)
// => maybe: 94.99873795683716 136.81783120735003 49.94186751166804,...
r = await sampleRandom('normal', { mu: 100, sigma: 50, low: 90 })
console.log(r)
// => maybe: 143.11557161592685 95.05143199643211 103.90352980637562,...
r = await sampleRandom('normal', { mu: 100, sigma: 50, low: 90, up: 110 })
console.log(r)
// => maybe: 99.45744560964987 95.98664948248341 95.69403830457458,...
r = await sampleRandom('normal', { mu: 0, sigma: 1, num: 5 })
console.log(r)
// => maybe: [
// 0.28480054449658343,
// -1.6656082612520913,
// -1.4973558587107332,
// 0.9279728382322514,
// 0.4704840133724234
// ]
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Attributes | Default | Description | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
name |
String | 輸入統計分布名稱 |
||||||||||||||||||||||
opt |
Object |
<optional> |
{}
|
輸入設定物件，預設{} Properties
|
Returns:
回傳亂數值或亂數值陣列
- Type
- Number | Array
(async, static) studentTInv(n, p) → {Number}
- Description:
基於Student-T累加分布計算指定位置之反函數值
Unit Test: Github
- Source:
Example
async function test() {
console.log(await studentTInv(35, 0.95))
// => 1.6909241978049958
console.log(await studentTInv(35, 0.5))
// => -0
console.log(await studentTInv(35, 0.05))
// => -1.6909241978049974
console.log(await studentTInv(15, 0.95))
// => 1.7613101151015698
}
test()
.catch((err) => {
console.log(err)
})Parameters:
| Name | Type | Description |
|---|---|---|
n |
Number | 輸入樣本數整數，需大於0 |
p |
Number | 輸入信賴水準浮點數，需介於0至1之間 |
Returns:
回傳反函數值
- Type
- Number