# JSXGraph 1.11.1 Reference

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# Namespace JXG.Math.ProbFuncs

↳ JXG.Math.ProbFuncs

Defined in: probfuncs.js.

Namespace Summary
Constructor Attributes | Constructor Name and Description
--- | ---
| JXG.Math.ProbFuncs Probability functions, e.g.

Method Summary
Method Attributes | Method Name and Description
--- | ---
<private> <static> | JXG.Math.ProbFuncs._underflow(a)
<static> | JXG.Math.ProbFuncs.erf(x) Error function SYNOPSIS: double x, y, erf(); y = erf( x ); DESCRIPTION: The integral is x - 2 | | 2 erf(x) = -------- | exp( - t ) dt.
<static> | JXG.Math.ProbFuncs.erfc(a) Complementary error function SYNOPSIS: double x, y, erfc(); y = erfc( x ); DESCRIPTION: 1 - erf(x) = inf.
<private> <static> | JXG.Math.ProbFuncs.erfce(x) Exponentially scaled erfc function exp(x^2) erfc(x) valid for x > 1.
<static> | JXG.Math.ProbFuncs.erfi(x) Inverse of error function erf.
<private> <static> | JXG.Math.ProbFuncs.expx2(x, sign) Exponential of squared argument SYNOPSIS: double x, y, expx2(); int sign; y = expx2( x, sign ); DESCRIPTION: Computes y = exp(x*x) while suppressing error amplification that would ordinarily arise from the inexactness of the exponential argument x*x.
<static> | JXG.Math.ProbFuncs.ndtr(a) Normal distribution function SYNOPSIS: y = ndtr( x ); DESCRIPTION: Returns the area under the Gaussian probability density function, integrated from minus infinity to x: x - 1 | | 2 ndtr(x) = --------- | exp( - t /2 ) dt sqrt(2pi) | | - -inf.
<static> | JXG.Math.ProbFuncs.ndtri(y0) Inverse of Normal distribution function SYNOPSIS: double x, y, ndtri(); x = ndtri( y ); DESCRIPTION: Returns the argument, x, for which the area under the Gaussian probability density function (integrated from minus infinity to x) is equal to y.
<private> <static> | JXG.Math.ProbFuncs.p1evl(x, coef, N) Evaluate polynomial when coefficient of x is 1.0.
<private> <static> | JXG.Math.ProbFuncs.polevl(x, coef, N) Evaluate polynomial SYNOPSIS: int N; double x, y, coef[N+1], polevl[]; y = polevl( x, coef, N ); DESCRIPTION: Evaluates polynomial of degree N: 2 N y = C + C x + C x +.

Namespace Detail
JXG.Math.ProbFuncs
Probability functions, e.g. error function, see: https://en.wikipedia.org/wiki/Error_function Ported from by https://github.com/jeremybarnes/cephes/blob/master/cprob/ndtr.c, Cephes Math Library Release 2.9: November, 2000 Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
Method Detail
<private> <static> {Number} JXG.Math.ProbFuncs._underflow(a)

Parameters:
{Number} a

Returns:
  {Number}

<static> {Number} JXG.Math.ProbFuncs.erf(x)
Error function SYNOPSIS: double x, y, erf(); y = erf( x ); DESCRIPTION: The integral is x - 2 | | 2 erf(x) = -------- | exp( - t ) dt. sqrt(pi) | | - 0 For 0 <= |x| < 1, erf(x) = x * P4(x**2)/Q5(x**2); otherwise erf(x) = 1 - erfc(x). ACCURACY: Relative error: arithmetic domain # trials peak rms DEC 0,1 14000 4.7e-17 1.5e-17 IEEE 0,1 30000 3.7e-16 1.0e-16

Parameters:
{Number} x

Returns:
  {Number}

<static> {Number} JXG.Math.ProbFuncs.erfc(a)
Complementary error function SYNOPSIS: double x, y, erfc(); y = erfc( x ); DESCRIPTION: 1 - erf(x) = inf. - 2 | | 2 erfc(x) = -------- | exp( - t ) dt sqrt(pi) | | - x For small x, erfc(x) = 1 - erf(x); otherwise rational approximations are computed. A special function expx2.c is used to suppress error amplification in computing exp(-x^2). ACCURACY: Relative error: arithmetic domain # trials peak rms IEEE 0,26.6417 30000 1.3e-15 2.2e-16 ERROR MESSAGES: message condition value returned erfc underflow x > 9.231948545 (DEC) 0.0

Parameters:
{Number} a

Returns:
  {Number}

<private> <static> {Number} JXG.Math.ProbFuncs.erfce(x)
Exponentially scaled erfc function exp(x^2) erfc(x) valid for x > 1. Use with ndtr and expx2.

Parameters:
{Number} x

Returns:
  {Number}

<static> {Number} JXG.Math.ProbFuncs.erfi(x)
Inverse of error function erf.

Parameters:
{Number} x

Returns:
  {Number}

<private> <static> {Number} JXG.Math.ProbFuncs.expx2(x, sign)
Exponential of squared argument SYNOPSIS: double x, y, expx2(); int sign; y = expx2( x, sign ); DESCRIPTION: Computes y = exp(x*x) while suppressing error amplification that would ordinarily arise from the inexactness of the exponential argument x*x. If sign < 0, the result is inverted; i.e., y = exp(-x*x) . ACCURACY: Relative error: arithmetic domain # trials peak rms IEEE -26.6, 26.6 10^7 3.9e-16 8.9e-17

Parameters:
{Number} x
{Number} sign
  (int)

Returns:
  {Number}

<static> {Number} JXG.Math.ProbFuncs.ndtr(a)
Normal distribution function SYNOPSIS: y = ndtr( x ); DESCRIPTION: Returns the area under the Gaussian probability density function, integrated from minus infinity to x: x - 1 | | 2 ndtr(x) = --------- | exp( - t /2 ) dt sqrt(2pi) | | - -inf. = ( 1 + erf(z) ) / 2 = erfc(z) / 2 where z = x/sqrt(2). Computation is via the functions erf and erfc with care to avoid error amplification in computing exp(-x^2). ACCURACY: Relative error: arithmetic domain # trials peak rms IEEE -13,0 30000 1.3e-15 2.2e-16 ERROR MESSAGES: message condition value returned erfc underflow x > 37.519379347 0.0

Parameters:
{Number} a

Returns:
  {Number}

<static> {Number} JXG.Math.ProbFuncs.ndtri(y0)
Inverse of Normal distribution function SYNOPSIS: double x, y, ndtri(); x = ndtri( y ); DESCRIPTION: Returns the argument, x, for which the area under the Gaussian probability density function (integrated from minus infinity to x) is equal to y. For small arguments 0 < y < exp(-2), the program computes z = sqrt( -2.0 * log(y) ); then the approximation is x = z - log(z)/z - (1/z) P(1/z) / Q(1/z). There are two rational functions P/Q, one for 0 < y < exp(-32) and the other for y up to exp(-2). For larger arguments, w = y - 0.5, and x/sqrt(2pi) = w + w**3 R(w**2)/S(w**2)). ACCURACY: Relative error: arithmetic domain # trials peak rms DEC 0.125, 1 5500 9.5e-17 2.1e-17 DEC 6e-39, 0.135 3500 5.7e-17 1.3e-17 IEEE 0.125, 1 20000 7.2e-16 1.3e-16 IEEE 3e-308, 0.135 50000 4.6e-16 9.8e-17 ERROR MESSAGES: message condition value returned ndtri domain x <= 0 -MAXNUM ndtri domain x >= 1 MAXNUM

Parameters:
{Number} y0

Returns:
  {Number}

<private> <static> {Number} JXG.Math.ProbFuncs.p1evl(x, coef, N)
Evaluate polynomial when coefficient of x is 1.0. Otherwise same as polevl.

Parameters:
{Number} x
{Number} coef
{Number} N

Returns:
  {Number}

<private> <static> {Number} JXG.Math.ProbFuncs.polevl(x, coef, N)
Evaluate polynomial SYNOPSIS: int N; double x, y, coef[N+1], polevl[]; y = polevl( x, coef, N ); DESCRIPTION: Evaluates polynomial of degree N: 2 N y = C + C x + C x +...+ C x 0 1 2 N Coefficients are stored in reverse order: coef[0] = C , ..., coef[N] = C . N 0 The function p1evl() assumes that coef[N] = 1.0 and is omitted from the array. Its calling arguments are otherwise the same as polevl(). SPEED: In the interest of speed, there are no checks for out of bounds arithmetic. This routine is used by most of the functions in the library. Depending on available equipment features, the user may wish to rewrite the program in microcode or assembly language.

Parameters:
{Number} x
{Number} coef
{Number} N

Returns:
  {Number}

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