Scilab Website | Contribute with GitLab | Mailing list archives | ATOMS toolboxes
Scilab Online Help
2023.1.0 - Português


cdfchn

cumulative distribution function non-central chi-square distribution

Syntax

[P,Q]=cdfchn("PQ",X,Df,Pnonc)
[X]=cdfchn("X",Df,Pnonc,P,Q);
[Df]=cdfchn("Df",Pnonc,P,Q,X)
[Pnonc]=cdfchn("Pnonc",P,Q,X,Df)

Arguments

P,Q,X,Df,Pnonc

five real vectors of the same size.

P,Q (Q=1-P)

The integral from 0 to X of the non-central chi-square distribution. Input range: [0, 1-1E-16).

X

Upper limit of integration of the non-central chi-square distribution. Input range: [0, +infinity). Search range: [0,1E300]

Df

Degrees of freedom of the non-central chi-square distribution. Input range: (0, +infinity). Search range: [ 1E-300, 1E300]

Pnonc

Non-centrality parameter of the non-central chi-square distribution. Input range: [0, +infinity). Search range: [0,1E4]

Description

Calculates any one parameter of the non-central chi-square distribution given values for the others.

Formula 26.4.25 of Abramowitz and Stegun, Handbook of Mathematical Functions (1966) is used to compute the cumulative distribution function.

Computation of other parameters involve a search for a value that produces the desired value of P. The search relies on the monotonicity of P with the other parameter.

The computation time required for this routine is proportional to the noncentrality parameter (PNONC). Very large values of this parameter can consume immense computer resources. This is why the search range is bounded by 10,000.

In certain cases, the degrees of freedom are not integers. Scilab then issues a warning.

From DCDFLIB: Library of Fortran Routines for Cumulative Distribution Functions, Inverses, and Other Parameters (February, 1994) Barry W. Brown, James Lovato and Kathy Russell. The University of Texas.

Examples

In the following example, we compute the probability of the event x=0.1 for the non-central chi-square distribution function with Df=2 and Pnonc=5.

Pnonc = 5;
Df = 2;
x = 0.1;
// Expected : P = 0.0042567 and Q = 1-P
[P, Q] = cdfchn("PQ", x, Df, Pnonc)

See also

  • cdfbet — cumulative distribution function Beta distribution
  • cdfbin — cumulative distribution function Binomial distribution
  • cdfchi — cumulative distribution function chi-square distribution
  • cdff — cumulative distribution function Fisher distribution
  • cdffnc — cumulative distribution function non-central f-distribution
  • cdfgam — cumulative distribution function gamma distribution
  • cdfnbn — cumulative distribution function negative binomial distribution
  • cdfnor — cumulative distribution function normal distribution
  • cdfpoi — cumulative distribution function poisson distribution
  • cdft — cumulative distribution function Student's T distribution
Report an issue
<< cdfchi Cumulated Distribution Functions cdff >>

Copyright (c) 2022-2024 (Dassault Systèmes)
Copyright (c) 2017-2022 (ESI Group)
Copyright (c) 2011-2017 (Scilab Enterprises)
Copyright (c) 1989-2012 (INRIA)
Copyright (c) 1989-2007 (ENPC)
with contributors
Last updated:
Mon May 22 12:42:13 CEST 2023