Methods
WDistributions() → {Object}
- Source:
計算Uniform、Normal、Binomial、Studentt分佈參數
因原版distributions使用cephes時未用compiled方式來支援瀏覽器, 且cephes內有使用node的Buffer, 需配合node polyfill編譯才能給前端瀏覽器使用
Fork: distributions
Unit Test: Github
Example
//import wd from './src/WDistributions.mjs'
//import wd from './dist/w-distributions.umd.js'
//import wd from 'w-distributions'
async function test() {
let r
let normal = await wd.Normal(1,2) //mean=1,std deviation=2
r = normal.pdf(1)
console.log(r)
// => 0.19947114020071632
r = normal.cdf(1)
console.log(r)
// => 0.5
r = normal.inv(1)
console.log(r)
// => Infiniy
r = normal.mean()
console.log(r)
// => 1
r = normal.median()
console.log(r)
// => 1
r = normal.variance()
console.log(r)
// => 4
//compare with: https://stattrek.com/online-calculator/t-distribution.aspx
let studentt = await wd.Studentt(34) //degrees of freedom=34
r = studentt.inv(0.95) //one or two sided test p-values=0.95
console.log(r)
// => 1.6909242551868549
studentt = await wd.Studentt(4) //degrees of freedom=4
r = studentt.inv(0.05) //one or two sided test p-values=0.05
console.log(r)
// => -2.1318467863266504
}
test()
.catch((err) => {
console.log(err)
})
Returns:
回傳各分佈初始化函數
- Type
- Object