feat(binomial-cdf): add binomial cumulative distribution function implementation

Author: Aadish Jain

lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/README.md

@@ -167,6 +167,91 @@ for ( i = 0; i < 10; i++ ) {
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dists/arcsine/cdf.h"
+```
+
+#### stdlib_base_dists_binomial_cdf( k, n, p )
+
+Evaluates the cumulative distribution function (CDF) for a binomial distribution.
+
+```c
+double out = stdlib_base_dists_binomial_cdf( 5, 10, 0.5 );
+// returns ~0.623
+```
+
+The function accepts the following arguments:
+
+-   **k**: `[in] int` input value
+-   **n**: `[in] int` number of trials
+-   **p**: `[in] double` success probability
+
+```c
+
+double stdlib_base_dists_binomial_cdf( const int k, const int n, const double p );
+
+```
+
+</section>
+<!-- /.usage -->
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+<section class="notes">
+</section>
+<!-- /.notes -->
+<!-- C API usage examples. -->
+<section class="examples">
+### Examples
+```c
+#include "stdlib/stats/base/dists/binomial/cdf.h"
+#include <stdlib.h>
+#include <stdio.h>
+int main( void ) {
+    int k;
+    int n;
+    double p;
+    double y;
+    int i;
+    
+    for ( i = 0; i < 25; i++ ) {
+        k = rand() % 11; // Random integer between 0 and 10
+        n = k + rand() % (21 - k); // Random integer between k and 20
+        p = ( (double)rand() / (double)RAND_MAX ); // Random double between 0.0 and 1.0
+        y = stdlib_base_dists_binomial_cdf( k, n, p );
+        printf( "k: %d, n: %d, p: %lf, F(k;n,p): %lf\n", k, n, p, y );
+    }
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">

lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/benchmark.js

@@ -21,7 +21,9 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var ceil = require( '@stdlib/math/base/special/ceil' );
+var Float64Array = require( '@stdlib/array/float64' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var randint = require( '@stdlib/random/array/randu' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pkg = require( './../package.json' ).name;
@@ -30,55 +32,72 @@ var cdf = require( './../lib' );
 
 // MAIN //
 
-bench( pkg, function benchmark( b ) {
+bench( pkg, function benchmark( b )
+{
+	var len;
+	var k;
 	var n;
 	var p;
-	var x;
 	var y;
 	var i;
 
+	len = 100;
+	k = new Float64Array( len );
+	n = new Float64Array( len );
+	p = new Float64Array( len );
+	for ( i = 0; i < len; i++ )
+	{
+		k[ i ] = randint( 0, 10 );
+		n[ i ] = randint( k[ i ], 20 );
+		p[ i ] = randu();
+	}
+
 	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		x = randu() * 100.0;
-		n = ceil( randu()*100.0 );
-		p = randu();
-		y = cdf( x, n, p );
-		if ( isnan( y ) ) {
+	for ( i = 0; i < b.iterations; i++ )
+	{
+		y = cdf( k[ i % len ], n[ i % len ], p[ i % len ] );
+		if ( isnan( y ) )
+		{
 			b.fail( 'should not return NaN' );
 		}
 	}
 	b.toc();
-	if ( isnan( y ) ) {
+	if ( isnan( y ) )
+	{
 		b.fail( 'should not return NaN' );
 	}
 	b.pass( 'benchmark finished' );
 	b.end();
-});
+} );
 
-bench( pkg+':factory', function benchmark( b ) {
+bench( pkg + ':factory', function benchmark( b )
+{
 	var mycdf;
 	var n;
 	var p;
-	var x;
+	var k;
 	var y;
 	var i;
 
-	n = 80;
-	p = 0.4;
+	n = 10;
+	p = 0.5;
 	mycdf = cdf.factory( n, p );
+	k = uniform( 100, 0, n );
 
 	b.tic();
-	for ( i = 0; i < b.iterations; i++ ) {
-		x = randu() * 80.0;
-		y = mycdf( x );
-		if ( isnan( y ) ) {
+	for ( i = 0; i < b.iterations; i++ )
+	{
+		y = mycdf( k[ i % k.length ] );
+		if ( isnan( y ) )
+		{
 			b.fail( 'should not return NaN' );
 		}
 	}
 	b.toc();
-	if ( isnan( y ) ) {
+	if ( isnan( y ) )
+	{
 		b.fail( 'should not return NaN' );
 	}
 	b.pass( 'benchmark finished' );
 	b.end();
-});
+} );

lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/benchmark.native.js

@@ -0,0 +1,79 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
+var randint = require( '@stdlib/random/base/randu' );
+var randu = require( '@stdlib/random/base/randu' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( cdf instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg, opts, function benchmark( b )
+{
+	var len;
+	var k;
+	var n;
+	var p;
+	var y;
+	var i;
+
+	len = 100;
+	k = new Float64Array( len );
+	n = new Float64Array( len );
+	p = new Float64Array( len );
+	for ( i = 0; i < len; i++ )
+	{
+		k[ i ] = randint( 0, 10 );
+		n[ i ] = randint( k[ i ], 20 );
+		p[ i ] = randu();
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ )
+	{
+		y = cdf( k[ i % len ], n[ i % len ], p[ i % len ] );
+		if ( isnan( y ) )
+		{
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) )
+	{
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+} );