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# CDF

Evaluates the F distribution CDF
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## CDF

 doubleCDF( int m int n double x bool upper` = 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

 m 1st number of degrees of freedom, must be strictly positive n 2nd number of degrees of freedom, must be strictly positive x the value at which to evaluate the function, must be positive upper Default 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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