feat: add c implementation for stats/base/dists/negative-binomial/pmf

lib/node_modules/@stdlib/stats/base/dists/negative-binomial/pmf/README.md

@@ -39,7 +39,7 @@ f(x; r, p) = P(X = x; r,p) = \binom{k+r-1}{x} p^r(1-p)^x \quad\text{for }x = 0,
 
 <!-- </equation> -->
 
-where `r > 0` is the number of successes until experiment is stopped and `0 < p <= 1` is the success probability. The random variable `X` denotes the number of failures until the `r` success is reached. 
+where `r > 0` is the number of successes until experiment is stopped and `0 < p <= 1` is the success probability. The random variable `X` denotes the number of failures until the `r` success is reached.
 
 </section>
 
@@ -161,6 +161,102 @@ 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/negative-binomial/pmf.h"
+```
+
+#### stdlib_base_dists_negative_binomial_mode( x, r, p )
+
+Evaluates the probability mass function (PMF) for a negative binomial distribution with number of successes until experiment is stopped `r` and success probability `p`.
+
+```c
+ double y = stdlib_base_dists_negative_binomial_mode( 5.0, 20.0, 0.8 );
+// returns ~0.157
+```
+
+The function accepts the following arguments:
+
+-   **x**: `[in] double` input value.
+-   **r**: `[in] double` number of failures until experiment is stopped .
+-   **p**: `[in] double` success probability .
+
+```c
+double stdlib_base_dists_negative_binomial_mode( const double x, const double r, 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/negative-binomial/pmf.h"
+#include "stdlib/math/base/special/round.h"
+#include "stdlib/constants/float64/eps"
+#include <stdlib.h>
+#include <stdio.h>
+
+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 x;
+   double r;
+   double p;
+   double y;
+   int i;
+
+    for ( i = 0; i < 10; i++ ) {
+        x =  stdlib_base_round( random_uniform( 0.0, 30.0 ) );
+        r = random_uniform( 0.0, 50.0 );
+        p = random_uniform( 0.0, 1.0 );
+        y = stdlib_base_dists_negative_binomial_pmf( x, r, p );
+        printf("x: %f, r: %f, p: %.4f, P(X=x;r,p): %.4f\n", x, r, p, y);
+    }
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
 <!-- 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/negative-binomial/pmf/benchmark/benchmark.js

@@ -21,9 +21,9 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var ceil = require( '@stdlib/math/base/special/ceil' );
+var Float64Array = require( '@stdlib/array/float64' );
+var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
 var uniform = require( '@stdlib/random/base/uniform' );
-var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
 var pkg = require( './../package.json' ).name;
@@ -33,18 +33,26 @@ var pmf = require( './../lib' );
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var r;
 	var p;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
+	x = new Float64Array( len );
+	r = new Float64Array( len );
+	p = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = discreteUniform( 0.0, 100.0 );
+		r[ i ] = discreteUniform( 0.0, 100.0 );
+		p[ i ] = uniform( EPS, 1.0 );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = ceil( randu()*100.0 );
-		r = ceil( randu()*100.0 );
-		p = uniform( EPS, 1.0 );
-		y = pmf( x, r, p );
+		y = pmf( x[ i % len ], r[ i % len ], p[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -59,20 +67,26 @@ bench( pkg, function benchmark( b ) {
 
 bench( pkg+':factory', function benchmark( b ) {
 	var mypmf;
+	var len;
 	var r;
 	var p;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
 	r = 80;
 	p = 0.4;
 	mypmf = pmf.factory( r, p );
+	x = new Float64Array( len );
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = uniform( 0.0, 80.0 );
+	}
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = ( randu()*80 );
-		y = mypmf( x );
+		y = mypmf( x[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}

lib/node_modules/@stdlib/stats/base/dists/negative-binomial/pmf/benchmark/benchmark.native.js

@@ -0,0 +1,75 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 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 tryRequire = require( '@stdlib/utils/try-require' );
+var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var pmf = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( pmf instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg+'::native', opts, function benchmark( b ) {
+	var len;
+	var r;
+	var p;
+	var x;
+	var y;
+	var i;
+
+	len = 100;
+	x = new Float64Array( len );
+	r = new Float64Array( len );
+	p = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = discreteUniform( 0.0, 100.0 );
+		r[ i ] = discreteUniform( 0.0, 100.0 );
+		p[ i ] = uniform( EPS, 1.0 );
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = pmf( x[ i % len ], r[ 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();
+});