stdlib-js
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About stdlib...
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Cumulative Distribution Function
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[Binomial][binomial-distribution] distribution [cumulative distribution function][cdf].
n is the number of trials and p is the success probability. The CDF can be equivalently expressed as
where I is the [lower regularized incomplete beta function][incomplete-beta].
bash
npm install @stdlib/stats-base-dists-binomial-cdf
javascript
var cdf = require( '@stdlib/stats-base-dists-binomial-cdf' );
#### cdf( x, n, p )
Evaluates the [cumulative distribution function][cdf] for a [binomial][binomial-distribution] distribution with number of trials n and success probability p.
javascript
var y = cdf( 3.0, 20, 0.2 );
// returns ~0.411
y = cdf( 21.0, 20, 0.2 );
// returns 1.0
y = cdf( 5.0, 10, 0.4 );
// returns ~0.834
y = cdf( 0.0, 10, 0.4 );
// returns ~0.006
If provided NaN as any argument, the function returns NaN.
javascript
var y = cdf( NaN, 20, 0.5 );
// returns NaN
y = cdf( 0.0, NaN, 0.5 );
// returns NaN
y = cdf( 0.0, 20, NaN );
// returns NaN
If provided a number of trials n which is not a nonnegative integer, the function returns NaN.
javascript
var y = cdf( 2.0, 1.5, 0.5 );
// returns NaN
y = cdf( 2.0, -2.0, 0.5 );
// returns NaN
If provided a success probability p outside of [0,1], the function returns NaN.
javascript
var y = cdf( 2.0, 20, -1.0 );
// returns NaN
y = cdf( 2.0, 20, 1.5 );
// returns NaN
#### cdf.factory( n, p )
Returns a function for evaluating the [cumulative distribution function][cdf] of a [binomial][binomial-distribution] distribution with number of trials n and success probability p.
javascript
var mycdf = cdf.factory( 10, 0.5 );
var y = mycdf( 3.0 );
// returns ~0.172
y = mycdf( 1.0 );
// returns ~0.011
javascript
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var cdf = require( '@stdlib/stats-base-dists-binomial-cdf' );
var i;
var n;
var p;
var x;
var y;
for ( i = 0; i < 10; i++ ) {
x = randu() * 20.0;
n = round( randu() * 100.0 );
p = randu();
y = cdf( x, n, p );
console.log( 'x: %d, n: %d, p: %d, F(x;n,p): %d', x.toFixed( 4 ), n, p.toFixed( 4 ), y.toFixed( 4 ) );
}
