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Wilcoxon signed rank test statistic quantile function.
npm install @stdlib/stats-base-dists-signrank-quantile
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
branch (see README). - If you are using Deno, visit the
deno
branch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umd
branch (see README).
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To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
var quantile = require( '@stdlib/stats-base-dists-signrank-quantile' );
Evaluates the quantile function for the Wilcoxon signed rank test statistic with n
observations.
var y = quantile( 0.8, 5 );
// returns 11
y = quantile( 0.5, 3 );
// returns 3
If provided a probability p
outside the interval [0,1]
, the function returns NaN
.
var y = quantile( 1.9, 5 );
// returns NaN
y = quantile( -0.1, 5 );
// returns NaN
If provided NaN
as any argument, the function returns NaN
.
var y = quantile( NaN, 5 );
// returns NaN
y = quantile( 0.0, NaN);
// returns NaN
If not provided a positive integer for n
, the function returns NaN
.
var y = quantile( 0.4, -1.0 );
// returns NaN
y = quantile( 0.4, 3.7 );
// returns NaN
Returns a function for evaluating the quantile function of the Wilcoxon signed rank test statistic with n
observations.
var myQuantile = quantile.factory( 8 );
var y = myQuantile( 0.4 );
// returns 16
y = myQuantile( 1.0 );
// returns 36
var randint = require( '@stdlib/random-base-discrete-uniform' );
var randu = require( '@stdlib/random-base-randu' );
var quantile = require( '@stdlib/stats-base-dists-signrank-quantile' );
var n;
var p;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
p = randu();
n = randint( 1, 20 );
y = quantile( p, n );
console.log( 'p: %d, n: %d, Q(p;n): %d', p.toFixed( 4 ), n, y.toFixed( 4 ) );
}
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.
See LICENSE.
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