w-statistic
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A tool for statistical analysis.
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<h2><a href="index.html">Home</a></h2><h3>Classes</h3><ul><li><a href="w-statistic.html">w-statistic</a><ul class='methods'><li data-type='method'><a href="w-statistic.html#.arrAverage">arrAverage</a></li><li data-type='method'><a href="w-statistic.html#.arrAverageWithLogNormCI">arrAverageWithLogNormCI</a></li><li data-type='method'><a href="w-statistic.html#.arrAverageWithNormCI">arrAverageWithNormCI</a></li><li data-type='method'><a href="w-statistic.html#.arrCount">arrCount</a></li><li data-type='method'><a href="w-statistic.html#.arrGammaFit">arrGammaFit</a></li><li data-type='method'><a href="w-statistic.html#.arrGammaHist">arrGammaHist</a></li><li data-type='method'><a href="w-statistic.html#.arrGammaInv">arrGammaInv</a></li><li data-type='method'><a href="w-statistic.html#.arrGeometricAverage">arrGeometricAverage</a></li><li data-type='method'><a href="w-statistic.html#.arrGeometricStd">arrGeometricStd</a></li><li data-type='method'><a href="w-statistic.html#.arrLogNormHist">arrLogNormHist</a></li><li data-type='method'><a href="w-statistic.html#.arrLogNormInv">arrLogNormInv</a></li><li data-type='method'><a href="w-statistic.html#.arrMovingAverage">arrMovingAverage</a></li><li data-type='method'><a href="w-statistic.html#.arrNormHist">arrNormHist</a></li><li data-type='method'><a href="w-statistic.html#.arrNormInv">arrNormInv</a></li><li data-type='method'><a href="w-statistic.html#.arrQuartile">arrQuartile</a></li><li data-type='method'><a href="w-statistic.html#.arrStd">arrStd</a></li><li data-type='method'><a href="w-statistic.html#.bin">bin</a></li><li data-type='method'><a href="w-statistic.html#.histGen">histGen</a></li><li data-type='method'><a href="w-statistic.html#.regLine">regLine</a></li><li data-type='method'><a href="w-statistic.html#.regMpLine">regMpLine</a></li><li data-type='method'><a href="w-statistic.html#.regPoly">regPoly</a></li><li data-type='method'><a href="w-statistic.html#.regPower">regPower</a></li><li data-type='method'><a href="w-statistic.html#.sampleRandom">sampleRandom</a></li><li data-type='method'><a href="w-statistic.html#.studentTInv">studentTInv</a></li></ul></li></ul>
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<h1 class="page-title">arrNormInv.mjs</h1>
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<pre class="prettyprint source linenums"><code>import size from 'lodash-es/size.js'
import isNumber from 'lodash-es/isNumber.js'
import isarr from 'wsemi/src/isarr.mjs'
import isnum from 'wsemi/src/isnum.mjs'
import cdbl from 'wsemi/src/cdbl.mjs'
import arrFilterByNum from 'wsemi/src/arrFilterByNum.mjs'
import arrAverage from './arrAverage.mjs'
import arrStd from './arrStd.mjs'
import jt from './jStat.mjs'
/**
* 基於常態累加分布計算指定位置之反函數值
*
* Unit Test: {@link https://github.com/yuda-lyu/w-statistic/blob/master/test/arrNormInv.test.js Github}
* @memberOf w-statistic
* @param {Array} arr 輸入陣列，只提取有效數字(或為字串的數字)進行計算
* @param {Number} ratio 輸入指定位置浮點數，需介於0至1之間
* @returns {Number} 回傳反函數值
* @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)
* })
*
*/
async function arrNormInv(arr, ratio) {
//check arr
if (!isarr(arr)) {
return Promise.reject('arr is not an array')
}
if (size(arr) === 0) {
return Promise.reject('arr is not an effective array')
}
//check ratio
if (!isnum(ratio)) {
return Promise.reject(`ratio[${ratio}] is not a number`)
}
ratio = cdbl(ratio)
if (ratio < 0) {
return Promise.reject(`ratio[${ratio}] < 0`)
}
if (ratio > 1) {
return Promise.reject(`ratio[${ratio}] > 1`)
}
//rs
let rs = arrFilterByNum(arr)
//n
let n = size(rs)
//check
if (n === 0) {
return Promise.reject(`no effective data`)
}
//avg, std
let avg = arrAverage(rs)
let std = arrStd(rs) //std為樣本標準差(用n-1)
// console.log('avg', avg, 'std', std)
//check avg
if (!isNumber(avg)) {
return Promise.reject(`avg[${avg}] is not a number`)
}
//check std
if (!isNumber(std)) {
return Promise.reject(`std[${std}] is not a number`)
}
//check std, 計算wd.Normal時標準差不能小於等於0
if (std <= 0) {
return Promise.reject(`std[${std}] <= 0`)
}
// //Normal
// let normal3_0025 = await wd.Normal(2.947834716, 0.025418535) //mean=2.947834716,arrStd deviation=0.025418535
// let r = normal3_0025.inv(0.25)
// console.log(`normal3_0025.inv(0.25)`, r)
// // => 2.9306901746775
//r, 等同於Excel的r=NORM.INV(p,mean,arrStd)
// let nm = await wd.Normal(avg, std)
// let r = nm.inv(ratio)
let r = jt.normal.inv(ratio, avg, std)
return {
inv: r,
avg,
std,
arr: rs,
}
}
export default arrNormInv
</code></pre>
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