@stdlib/stats-base-dists-chi-cdf
v0.3.1
Published
Chi distribution cumulative distribution function (CDF).
Readme
Cumulative Distribution Function
Chi distribution cumulative distribution function.
The cumulative distribution function for a chi random variable is
where k is the degrees of freedom and P is the lower regularized incomplete gamma function.
Installation
npm install @stdlib/stats-base-dists-chi-cdfUsage
var cdf = require( '@stdlib/stats-base-dists-chi-cdf' );cdf( x, k )
Evaluates the cumulative distribution function (CDF) for a chi distribution with degrees of freedom k.
var y = cdf( 2.0, 1.0 );
// returns ~0.954
y = cdf( 2.0, 3.0 );
// returns ~0.739
y = cdf( 1.0, 0.5 );
// returns ~0.846
y = cdf( -1.0, 2.0 );
// returns 0.0
y = cdf( -Infinity, 4.0 );
// returns 0.0
y = cdf( +Infinity, 4.0 );
// returns 1.0If provided NaN as any argument, the function returns NaN.
var y = cdf( NaN, 1.0 );
// returns NaN
y = cdf( 0.0, NaN );
// returns NaNIf provided k < 0, the function returns NaN.
var y = cdf( 2.0, -2.0 );
// returns NaNIf provided k = 0, the function evaluates the CDF of a degenerate distribution centered at 0.
var y = cdf( 2.0, 0.0 );
// returns 1.0
y = cdf( -2.0, 0.0 );
// returns 0.0
y = cdf( 0.0, 0.0 );
// returns 1.0cdf.factory( k )
Returns a function for evaluating the cumulative distribution function for a chi distribution with degrees of freedom k.
var mycdf = cdf.factory( 3.0 );
var y = mycdf( 6.0 );
// returns ~1.0
y = mycdf( 1.5 );
// returns ~0.478C APIs
Usage
#include "stdlib/stats/base/dists/chi/cdf.h"stdlib_base_dists_chi_cdf( x, k )
Evaluates the cumulative distribution function (CDF) for a chi distribution with degrees of freedom k.
double out = stdlib_base_dists_chi_cdf( 2.0, 1.0 );
// returns ~0.954
out = stdlib_base_dists_chi_cdf( 2.0, 3.0 );
// returns ~0.739The function accepts the following arguments:
- x:
[in] doubleinput value. - k:
[in] doubledegrees of freedom.
double stdlib_base_dists_chi_cdf( const double x, const double k );Examples
#include "stdlib/stats/base/dists/chi/cdf.h"
#include <stdlib.h>
#include <stdio.h>
static double random_uniform( double a, double b ) {
double r = ( (double)rand() / ( (double)RAND_MAX + 1.0 ) );
return a + ( r * ( b - a ) );
}
int main( void ) {
double x;
double k;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
x = random_uniform( 0.0, 2.0 );
k = random_uniform( 1.0, 10.0 );
y = stdlib_base_dists_chi_cdf( x, k );
printf( "x: %lf, k: %lf, F(x;k): %lf\n", x, k, y );
}
}Examples
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var cdf = require( '@stdlib/stats-base-dists-chi-cdf' );
var opts = {
'dtype': 'float64'
};
var x = uniform( 20, 0.0, 10.0, opts );
var k = discreteUniform( 20, 0, 10, opts );
logEachMap( 'x: %0.4f, k: %d, F(x;k): %0.4f', x, k, cdf );Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
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License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
