Raised cosine distribution quantile function.
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> [Raised cosine][cosine-distribution] distribution [quantile function][quantile-function].
``bash`
npm install @stdlib/stats-base-dists-cosine-quantile
`javascript`
var quantile = require( '@stdlib/stats-base-dists-cosine-quantile' );
#### quantile( p, mu, s )
Evaluates the [quantile function][quantile-function] for a [raised cosine][cosine-distribution] distribution with parameters mu (location parameter) and s (scale parameter).
`javascript
var y = quantile( 0.5, 0.0, 1.0 );
// returns ~0.0
y = quantile( 0.2, 4.0, 2.0 );
// returns ~3.345
`
If provided a probability p outside the interval [0,1], the function returns NaN.
`javascript
var y = quantile( 1.9, 0.0, 1.0 );
// returns NaN
y = quantile( -0.1, 0.0, 1.0 );
// returns NaN
`
If provided NaN as any argument, the function returns NaN.
`javascript
var y = quantile( NaN, 0.0, 1.0 );
// returns NaN
y = quantile( 0.0, NaN, 1.0 );
// returns NaN
y = quantile( 0.0, 0.0, NaN );
// returns NaN
`
If provided s < 0, the function returns NaN.
`javascript`
var y = quantile( 0.4, 0.0, -1.0 );
// returns NaN
If provided s = 0, the function evaluates the [quantile function][quantile-function] of a [degenerate distribution][degenerate-distribution] centered at mu.
`javascript
var y = quantile( 0.3, 8.0, 0.0 );
// returns 8.0
y = quantile( 0.9, 8.0, 0.0 );
// returns 8.0
`
#### quantile.factory( mu, s )
Returns a function for evaluating the [quantile function][quantile-function] of a [raised cosine][cosine-distribution] distribution with parameters mu and s.
`javascript
var myQuantile = quantile.factory( 10.0, 2.0 );
var y = myQuantile( 0.2 );
// returns ~9.345
y = myQuantile( 0.9 );
// returns ~10.964
`
`javascript
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var quantile = require( '@stdlib/stats-base-dists-cosine-quantile' );
var opts = {
'dtype': 'float64'
};
var p = uniform( 10, 0.0, 1.0, opts );
var mu = uniform( 10, 0.0, 10.0, opts );
var s = uniform( 10, 0.0, 10.0, opts );
logEachMap( 'p: %0.4f, µ: %0.4f, s: %0.4f, Q(p;µ,s): %0.4f', p, mu, s, quantile );
`
*
`c`
#include "stdlib/stats/base/dists/cosine/quantile.h"
#### stdlib_base_dists_cosine_quantile( p, mu, s )
Evaluates the [quantile function][quantile-function] for a [raised cosine][cosine-distribution] distribution with parameters mu (location parameter) and s (scale parameter).
`c`
double out = stdlib_base_dists_cosine_quantile( 0.8, 0.0, 1.0 );
// returns ~0.327
The function accepts the following arguments:
- p: [in] double input value.[in] double
- mu: location parameter.[in] double
- s: scale parameter.
`c`
double stdlib_base_dists_cosine_quantile( const double p, const double mu, const double s );
`c
#include "stdlib/stats/base/dists/cosine/quantile.h"
#include "stdlib/constants/float64/eps.h"
#include
#include
static double random_uniform( const double min, const double max ) {
double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
return min + ( v*(max-min) );
}
int main( void ) {
double mu;
double s;
double p;
double y;
int i;
for ( i = 0; i < 10; i++ ) {
p = random_uniform( 0.0, 1.0 );
mu = random_uniform( -50.0, 50.0 );
s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 );
y = stdlib_base_dists_cosine_quantile( p, mu, s );
printf( "p: %.4f, µ: %.4f, s: %.4f, Q(p;µ,s): %.4f\n", p, mu, s, y );
}
return 0;
}
`
*
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
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---
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[cosine-distribution]: https://en.wikipedia.org/wiki/Raised_cosine_distribution
[quantile-function]: https://en.wikipedia.org/wiki/Quantile_function
[degenerate-distribution]: https://en.wikipedia.org/wiki/Degenerate_distribution