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cdffnc

cumulative distribution function non-central f-distribution

Syntax

[P,Q]=cdffnc("PQ",F,Dfn,Dfd,Pnonc)
[F]=cdffnc("F",Dfn,Dfd,Pnonc,P,Q);
[Dfn]=cdffnc("Dfn",Dfd,Pnonc,P,Q,F);
[Dfd]=cdffnc("Dfd",Pnonc,P,Q,F,Dfn)
[Pnonc]=cdffnc("Pnonc",P,Q,F,Dfn,Dfd);

Arguments

P,Q,F,Dfn,Dfd,Pnonc

six real vectors of the same size.

P,Q (Q=1-P)

The integral from 0 to F of the non-central f-density. Input range: [0,1-1E-16).

F

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

Dfn

Degrees of freedom of the numerator sum of squares. Input range: (0, +infinity). Search range: [ 1E-300, 1E300]

Dfd

Degrees of freedom of the denominator sum of squares. Must be in range: (0, +infinity). Input range: (0, +infinity). Search range: [ 1E-300, 1E300]

Pnonc

The non-centrality parameter Input range: [0,infinity) Search range: [0,1E4]

Description

Calculates any one parameter of the Non-central F distribution given values for the others.

Formula 26.6.20 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.

The value of the cumulative noncentral F distribution is not necessarily monotone in either degrees of freedom. There thus may be two values that provide a given CDF value. This routine assumes monotonicity and will find an arbitrary one of the two values.

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

f        = [1:2];
dfn      = [1:2];
dfd      = 2*dfn;
pn       = [0,1];

[P,Q]    = cdffnc("PQ",f,dfn,dfd,pn)

See also

  • cdfbet — cumulative distribution function Beta distribution
  • cdfbin — cumulative distribution function Binomial distribution
  • cdfchi — cumulative distribution function chi-square distribution
  • cdfchn — cumulative distribution function non-central chi-square distribution
  • cdff — cumulative distribution function Fisher 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
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