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CDF

Evaluates the F distribution CDF
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Dependents

Info

Interface

C++
Excel

CDF

 
doubleCDFintm
intn
doublex
boolupper = false )
This function evaluates the F distribution CDF.

Accuracy:

Tested at random points (m,n,x).
domain x  domain m,n  # trials     peak         rms
  0,1      1,100       100000     3.7e-14     5.9e-16
  1,5      1,100       100000     8.0e-15     1.6e-15
  0,1      1,10000     100000     1.8e-11     3.5e-13
  1,5      1,10000     100000     2.0e-11     3.0e-12

Example:

#include <stdio.h>
#include <codecogs/stats/dists/continuous/f/cdf.h>
using namespace Stats::Dists::Continuous::F;
int main()
{
  int m[10] = { 7, 7, 6, 7, 6, 7, 9, 9, 1, 11 };
  int n[10] = { 5, 8, 3, 7, 5, 5, 4, 5, 11, 8 };
  double x[10] = {0.3, 0.6, 0.9, 0.6, 0.1, 0.4, 0.8, 0.3, 1.0, 0.2 };
  for( int i=0; i<10; i++ )
    printf(  "CDF( %i, %i, %1.1f, true ) = %f \n",
      m[i], n[i], x[i], CDF( m[i], n[i], x[i] )  );
  return getchar();
}

Output:

CDF( 7, 5, 0.3, true ) = 0.926089
CDF( 7, 8, 0.6, true ) = 0.742601
CDF( 6, 3, 0.9, true ) = 0.584629
CDF( 7, 7, 0.6, true ) = 0.741755
CDF( 6, 5, 0.1, true ) = 0.992880
CDF( 7, 5, 0.4, true ) = 0.867994
CDF( 9, 4, 0.8, true ) = 0.642990
CDF( 9, 5, 0.3, true ) = 0.944103
CDF( 1, 11, 1.0, true ) = 0.338801
CDF( 11, 8, 0.2, true ) = 0.991790

Parameters

m1st number of degrees of freedom, must be strictly positive
n2nd number of degrees of freedom, must be strictly positive
xthe value at which to evaluate the function, must be positive
upperDefault value = false

Authors

Stephen L. Moshier (June 2000)
Updated by Vince Cole and Eduard-Mihai Bentea
Source Code

Source code is available when you buy a Commercial licence.

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