26335051199

Committed 23 May 2026 02:19PM UTC coverage: 96.742% (+0.09%) from 96.649%

Build # 26335051199

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push

github

Committed by

web-flow

Commit Message

Merge pull request #361 from synesenom/claude/build-135-BYxKZ

Add second parameter cases to 105 single-case distributions

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960 of 1041 branches covered (92.22%)

Branch coverage included in aggregate %.

3197 of 3256 relevant lines covered (98.19%)

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92.59

/src/dist/tukey-lambda.js

import Distribution from './_distribution'
import brent from '../algorithms/brent'

/**
 * Generator for the [Tukey lambda distribution]{@link https://en.wikipedia.org/wiki/Tukey_lambda_distribution}:
 *
 * $f(x; \lambda) = \frac{1}{Q^{-1}(F(x))},$
 *
 * where $Q(p) = \frac{p^\lambda - (1 - p)^\lambda}{\lambda}$ and $F(x) = Q^{-1}(x)$. Support: $x \in \[-1/\lambda, 1/\lambda\]$ if $\lambda > 0$, otherwise $x \in \mathbb{R}$.
 *
 * @class TukeyLambda
 * @memberof ran.dist
 * @see https://en.wikipedia.org/wiki/Tukey_lambda_distribution
 * @constructor
 */
export default class TukeyLambda extends Distribution {
  /**
   * @param {number} lambda Shape parameter.
   */
  constructor (lambda) {
    super('continuous', 1)

    // Validate parameters
    this.p = { lambda }
    Distribution.validate({ lambda }, [])

    // Set support
    this.s = [{
      value: lambda > 0 ? -1 / lambda : -Infinity,
      closed: lambda > 0
    }, {
      value: lambda > 0 ? 1 / lambda : Infinity,
      closed: lambda > 0
    }]
  }

  _generator () {
    // Inverse transform sampling
    return this._q(this.r.next())
  }

  _pdf (x) {
    if (this.p.lambda === 0) {
      const y = Math.exp(-x)
      return y / Math.pow(1 + y, 2)
    } else {
      if (x === 0) {
        return Math.pow(2, this.p.lambda) / 4
      } else {
        // f(x) = Q^(-1)[F(x)]
        const z = this._cdf(x)
        return 1 / (Math.pow(z, this.p.lambda - 1) + Math.pow(1 - z, this.p.lambda - 1))
      }
    }
  }

  _cdf (x) {
    // If lambda != 0, F(x) is the inverse of quantile function
    return this.p.lambda === 0
      ? 1 / (1 + Math.exp(-x))
      : brent(
        t => (Math.pow(t, this.p.lambda) - Math.pow(1 - t, this.p.lambda)) / this.p.lambda - x,
        0, 1
      )
  }

  _q (p) {
    return this.p.lambda === 0
      ? Math.log(p / (1 - p))
      : (Math.pow(p, this.p.lambda) - Math.pow(1 - p, this.p.lambda)) / this.p.lambda
  }
}

1	import Distribution from './_distribution'
2	import brent from '../algorithms/brent'
3
4	/**
5	* Generator for the [Tukey lambda distribution]{@link https://en.wikipedia.org/wiki/Tukey_lambda_distribution}:
6	*
7	* $f(x; \lambda) = \frac{1}{Q^{-1}(F(x))},$
8	*
9	* where $Q(p) = \frac{p^\lambda - (1 - p)^\lambda}{\lambda}$ and $F(x) = Q^{-1}(x)$. Support: $x \in \[-1/\lambda, 1/\lambda\]$ if $\lambda > 0$, otherwise $x \in \mathbb{R}$.
10	*
11	* @class TukeyLambda
12	* @memberof ran.dist
13	* @see https://en.wikipedia.org/wiki/Tukey_lambda_distribution
14	* @constructor
15	*/
16	export default class TukeyLambda extends Distribution {
17	/**
18	* @param {number} lambda Shape parameter.
19	*/
20	constructor (lambda) {
21	super('continuous', 1)	52✔
22
23	// Validate parameters
24	this.p = { lambda }	52✔
25	Distribution.validate({ lambda }, [])	52✔
26
27	// Set support
28	this.s = [{	51✔
29	value: lambda > 0 ? -1 / lambda : -Infinity,	51✔
30	closed: lambda > 0
31	}, {
32	value: lambda > 0 ? 1 / lambda : Infinity,	51✔
33	closed: lambda > 0
34	}]
35	}
36
37	_generator () {
38	// Inverse transform sampling
39	return this._q(this.r.next())	170,630✔
40	}
41
42	_pdf (x) {
43	if (this.p.lambda === 0) {	54✔
44	const y = Math.exp(-x)	28✔
45	return y / Math.pow(1 + y, 2)	28✔
46	} else {
47	if (x === 0) {	26!
48	return Math.pow(2, this.p.lambda) / 4	×
49	} else {
50	// f(x) = Q^(-1)[F(x)]
51	const z = this._cdf(x)	26✔
52	return 1 / (Math.pow(z, this.p.lambda - 1) + Math.pow(1 - z, this.p.lambda - 1))	26✔
53	}
54	}
55	}
56
57	_cdf (x) {
58	// If lambda != 0, F(x) is the inverse of quantile function
59	return this.p.lambda === 0	90,483✔
60	? 1 / (1 + Math.exp(-x))
61	: brent(
62	t => (Math.pow(t, this.p.lambda) - Math.pow(1 - t, this.p.lambda)) / this.p.lambda - x,	139,792✔
63	0, 1
64	)
65	}
66
67	_q (p) {
68	return this.p.lambda === 0	170,847✔
69	? Math.log(p / (1 - p))
70	: (Math.pow(p, this.p.lambda) - Math.pow(1 - p, this.p.lambda)) / this.p.lambda
71	}
72	}

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