R's variance in TypeScript

How to use

Install via yarn add locutus and import: import { variance } from 'locutus/r/stats/variance'.

Or with CommonJS: const { variance } = require('locutus/r/stats/variance')

Use a bundler that supports tree-shaking so you only ship the functions you actually use. Vite, webpack, Rollup, and Parcel all handle this. For server-side use this is less of a concern.

Examples

These examples are extracted from test cases that automatically verify our functions against their native counterparts.

#	code	expected result
1	variance([1, 2, 3])	1
2	variance([1, 2, 3, 4])	1.6666666666666667
3	variance([2, 4, 6])	4

Notes

• JS-safe equivalent of R’s var() for a plain vector; matrix/data-frame forms are out of scope.

Dependencies

This function uses the following Locutus functions:

• _stats (r/_helpers)

Here's what our current TypeScript equivalent to R's variance looks like.

TSTypeScript JSJavaScript TSStandalone TS JSStandalone JS

Copy code

import { sampleVariance, toRNumericArray } from '../_helpers/_stats.ts'

export function variance(x: unknown): number {
  //      discuss at: https://locutus.io/r/variance/
  // parity verified: R 4.4
  //     original by: Kevin van Zonneveld (https://kvz.io)
  //          note 1: JS-safe equivalent of R's var() for a plain vector; matrix/data-frame forms are out of scope.
  //       example 1: variance([1, 2, 3])
  //       returns 1: 1
  //       example 2: variance([1, 2, 3, 4])
  //       returns 2: 1.6666666666666667
  //       example 3: variance([2, 4, 6])
  //       returns 3: 4

  return sampleVariance(toRNumericArray(x, 'variance'))
}

import { sampleVariance, toRNumericArray } from '../_helpers/_stats.ts'

export function variance(x) {
  //      discuss at: https://locutus.io/r/variance/
  // parity verified: R 4.4
  //     original by: Kevin van Zonneveld (https://kvz.io)
  //          note 1: JS-safe equivalent of R's var() for a plain vector; matrix/data-frame forms are out of scope.
  //       example 1: variance([1, 2, 3])
  //       returns 1: 1
  //       example 2: variance([1, 2, 3, 4])
  //       returns 2: 1.6666666666666667
  //       example 3: variance([2, 4, 6])
  //       returns 3: 4

  return sampleVariance(toRNumericArray(x, 'variance'))
}

// r/_helpers/_stats (Locutus helper dependency)
function toRNumericArray(data: unknown, functionName: string): number[] {
  if (!Array.isArray(data)) {
    throw new TypeError(`${functionName}() data must be an array`)
  }

  return data.map((value) => toRNumber(value, functionName))
}

function toRNumber(value: unknown, functionName: string): number {
  if (typeof value === 'number') {
    return value
  }

  if (typeof value === 'boolean') {
    return value ? 1 : 0
  }

  if (typeof value === 'bigint') {
    const numericValue = Number(value)
    if (!Number.isSafeInteger(numericValue)) {
      throw new RangeError(`${functionName}() bigint values must fit within JS safe integer precision`)
    }

    return numericValue
  }

  throw new TypeError(`${functionName}() data must contain only numeric values`)
}

function sampleVariance(values: number[]): number {
  if (values.length < 2) {
    return Number.NaN
  }

  const mean = values.reduce((sum, value) => sum + value, 0) / values.length
  const squaredDeltaSum = values.reduce((sum, value) => {
    const delta = value - mean
    return sum + delta * delta
  }, 0)

  return squaredDeltaSum / (values.length - 1)
}

// r/stats/variance (target function module)
function variance(x: unknown): number {
  //      discuss at: https://locutus.io/r/variance/
  // parity verified: R 4.4
  //     original by: Kevin van Zonneveld (https://kvz.io)
  //          note 1: JS-safe equivalent of R's var() for a plain vector; matrix/data-frame forms are out of scope.
  //       example 1: variance([1, 2, 3])
  //       returns 1: 1
  //       example 2: variance([1, 2, 3, 4])
  //       returns 2: 1.6666666666666667
  //       example 3: variance([2, 4, 6])
  //       returns 3: 4

  return sampleVariance(toRNumericArray(x, 'variance'))
}

// r/_helpers/_stats (Locutus helper dependency)
function toRNumericArray(data, functionName) {
  if (!Array.isArray(data)) {
    throw new TypeError(`${functionName}() data must be an array`)
  }

  return data.map((value) => toRNumber(value, functionName))
}

function toRNumber(value, functionName) {
  if (typeof value === 'number') {
    return value
  }

  if (typeof value === 'boolean') {
    return value ? 1 : 0
  }

  if (typeof value === 'bigint') {
    const numericValue = Number(value)
    if (!Number.isSafeInteger(numericValue)) {
      throw new RangeError(`${functionName}() bigint values must fit within JS safe integer precision`)
    }

    return numericValue
  }

  throw new TypeError(`${functionName}() data must contain only numeric values`)
}

function sampleVariance(values) {
  if (values.length < 2) {
    return Number.NaN
  }

  const mean = values.reduce((sum, value) => sum + value, 0) / values.length
  const squaredDeltaSum = values.reduce((sum, value) => {
    const delta = value - mean
    return sum + delta * delta
  }, 0)

  return squaredDeltaSum / (values.length - 1)
}

// r/stats/variance (target function module)
function variance(x) {
  //      discuss at: https://locutus.io/r/variance/
  // parity verified: R 4.4
  //     original by: Kevin van Zonneveld (https://kvz.io)
  //          note 1: JS-safe equivalent of R's var() for a plain vector; matrix/data-frame forms are out of scope.
  //       example 1: variance([1, 2, 3])
  //       returns 1: 1
  //       example 2: variance([1, 2, 3, 4])
  //       returns 2: 1.6666666666666667
  //       example 3: variance([2, 4, 6])
  //       returns 3: 4

  return sampleVariance(toRNumericArray(x, 'variance'))
}

Improve this function

Locutus is a community effort following The McDonald's Theory: we ship first iterations, hoping others will improve them. If you see something that could be better, we'd love your contribution.

View on GitHub · Edit on GitHub · View Raw

---

We have 22 R functions so far - help us add more

Got a rainy Sunday afternoon and a taste for a porting puzzle?

• Get inspiration from the R base documentation.
• Click "New file" in the appropriate folder on GitHub. This will fork the project to your account, directly add the file to it, and send a Pull Request to us.

We will then review it. If it's useful to the project and in line with our contributing guidelines your work will become part of Locutus and you'll be automatically credited in the authors section accordingly.

« More R stats functions

Star