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Author: stdlib-bot

CHANGELOG.md

@@ -4,7 +4,7 @@
 
 <section class="release" id="unreleased">
 
-## Unreleased (2024-12-23)
+## Unreleased (2024-12-24)
 
 <section class="packages">
 
@@ -2912,6 +2912,7 @@ A total of 17 people contributed to this release. Thank you to the following con
 
 <details>
 
+-   [`b7867cb`](https://github.com/stdlib-js/stdlib/commit/b7867cbb3a4fc453e19203794402c36f19b264fd) - **chore:** minor clean-up _(by Philipp Burckhardt)_
 -   [`62364f6`](https://github.com/stdlib-js/stdlib/commit/62364f62ea823a3b52c2ad25660ecd80c71f8f36) - **style:** fix C comment alignment _(by Philipp Burckhardt)_
 -   [`0ba282b`](https://github.com/stdlib-js/stdlib/commit/0ba282b89c384f06bbe3ff8ecd71982f05209606) - **chore:** minor clean-up _(by Philipp Burckhardt)_
 -   [`9f71ae0`](https://github.com/stdlib-js/stdlib/commit/9f71ae0ab3105190b6638768b83756e69d9146ea) - **chore:** address feedback and enable tests _(by Philipp Burckhardt)_

base/dists/bernoulli/mean/benchmark/c/benchmark.c

@@ -75,13 +75,15 @@ static double tic( void ) {
 }
 
 /**
-* Generates a random number on the interval [0,1).
+* Generates a random number on the interval [min,max).
 *
-* @return random number
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
 */
-static double rand_double( void ) {
-	int r = rand();
-	return (double)r / ( (double)RAND_MAX + 1.0 );
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
 }
 
 /**
@@ -97,7 +99,7 @@ static double benchmark( void ) {
 	int i;
 
 	for ( i = 0; i < 100; i++ ) {
-		p[ i ] = rand_double();
+		p[ i ] = random_uniform( 0.0, 1.0 );
 	}
 
 	t = tic();

base/dists/bernoulli/mode/benchmark/c/benchmark.c

@@ -75,13 +75,15 @@ static double tic( void ) {
 }
 
 /**
-* Generates a random number on the interval [0,1).
+* Generates a random number on the interval [min,max).
 *
-* @return random number
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
 */
-static double rand_double( void ) {
-	int r = rand();
-	return (double)r / ( (double)RAND_MAX + 1.0 );
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
 }
 
 /**
@@ -97,7 +99,7 @@ static double benchmark( void ) {
 	int i;
 
 	for ( i = 0; i < 100; i++ ) {
-		p[ i ] = rand_double();
+		p[ i ] = random_uniform( 0.0, 1.0 );
 	}
 
 	t = tic();

base/dists/exponential/mean/test/test.native.js

@@ -24,9 +24,7 @@ var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var abs = require( '@stdlib/math/base/special/abs' );
 var NINF = require( '@stdlib/constants/float64/ninf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 
 
 // VARIABLES //
@@ -68,25 +66,17 @@ tape( 'if provided a rate parameter `lambda` that is not a nonnegative number, t
 	t.end();
 });
 
-tape( 'the function returns the mean of an exponential distribution', opts, function test( t ) {
+tape( 'the function returns the expected value of an exponential distribution', opts, function test( t ) {
 	var expected;
 	var lambda;
-	var delta;
-	var tol;
 	var i;
 	var y;
 
 	expected = data.expected;
 	lambda = data.lambda;
 	for ( i = 0; i < expected.length; i++ ) {
 		y = mean( lambda[i] );
-		if ( y === expected[ i ] ) {
-			t.equal( y, expected[i], 'lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			delta = abs( y - expected[ i ] );
-			tol = 2.0 * EPS * abs( expected[ i ] );
-			t.ok( delta <= tol, 'within tolerance. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.equal( y, expected[i], 'lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
 	}
 	t.end();
 });

base/dists/f/skewness/benchmark/c/benchmark.c

@@ -102,7 +102,7 @@ static double benchmark( void ) {
 
 	for ( i = 0; i < 100; i++ ) {
 		d1[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
-		d2[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		d2[ i ] = random_uniform( 0.0, 10.0 ) + 6.0 + STDLIB_CONSTANT_FLOAT64_EPS;
 	}
 
 	t = tic();

base/dists/gamma/kurtosis/README.md

@@ -170,7 +170,7 @@ for ( i = 0; i < 10; i++ ) {
 
 #### stdlib_base_dists_gamma_kurtosis( alpha, beta )
 
-Returns the kurtosis of a gamma distribution.
+Returns the [excess kurtosis][kurtosis] of a [gamma][gamma-distribution] distribution with parameters `alpha` (shape parameter) and `beta` (rate parameter).
 
 ```c
 double out = stdlib_base_dists_gamma_kurtosis( 1.0, 1.0 );

base/dists/gamma/kurtosis/src/main.c

@@ -28,7 +28,7 @@
 *
 * @example
 * double y = stdlib_base_gamma_kurtosis( 1.0, 1.0 );
-* // returns 1.0
+* // returns 6.0
 */
 double stdlib_base_dists_gamma_kurtosis( const double alpha, const double beta ) {
 	if (

base/dists/gamma/mean/README.md

@@ -172,7 +172,7 @@ for ( i = 0; i < 10; i++ ) {
 
 #### stdlib_base_dists_gamma_mean( alpha, beta )
 
-Returns the mean of a gamma distribution.
+Returns the [expected value][expected-value] of a [gamma][gamma-distribution] distribution with parameters `alpha` (shape parameter) and `beta` (rate parameter).
 
 ```c
 double out = stdlib_base_dists_gamma_mean( 1.0, 1.0 );

base/dists/gamma/mean/include/stdlib/stats/base/dists/gamma/mean.h

@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Returns the mean of a gamma distribution.
+* Returns the expected value of a gamma distribution.
 */
 double stdlib_base_dists_gamma_mean( const double alpha, const double beta );
 

base/dists/gamma/mean/src/main.c

@@ -19,11 +19,11 @@
 #include "stdlib/stats/base/dists/gamma/mean.h"
 
 /**
-* Returns the mean of a gamma distribution.
+* Returns the expected value of a gamma distribution.
 *
 * @param alpha    shape parameter
 * @param beta     rate parameter
-* @return         mean
+* @return         expected value
 *
 * @example
 * double y = stdlib_base_gamma_mean( 1.0, 1.0 );

base/dists/gamma/mean/test/test.native.js

@@ -121,7 +121,7 @@ tape( 'the function returns the mean of a gamma distribution', opts, function te
 			t.equal( y, expected[i], 'alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] );
 		} else {
 			delta = abs( y - expected[ i ] );
-			tol = 2.0 * EPS * abs( expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
 			t.ok( delta <= tol, 'within tolerance. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
 		}
 	}

base/dists/poisson/mean/benchmark/c/benchmark.c

@@ -75,13 +75,15 @@ static double tic( void ) {
 }
 
 /**
-* Generates a random number on the interval [0,20).
+* Generates a random number on the interval [min,max).
 *
-* @return random number
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
 */
-static double rand_double( void ) {
-	int r = rand();
-	return 20.0*(double)r / ( (double)RAND_MAX + 1.0 );
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
 }
 
 /**
@@ -97,7 +99,7 @@ static double benchmark( void ) {
 	int i;
 
 	for ( i = 0; i < 100; i++ ) {
-		lambda[ i ] = rand_double();
+		lambda[ i ] = random_uniform( 0.0, 20.0 );
 	}
 
 	t = tic();

base/dists/triangular/mean/include/stdlib/stats/base/dists/triangular/mean.h

@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Returns the mean of a triangular distribution with lower bound `a`, upper bound `b`, and mode `c`.
+* Returns the mean of a triangular distribution.
 */
 double stdlib_base_dists_triangular_mean( const double a, const double b, const double c );
 

base/dists/triangular/mean/lib/native.js

@@ -29,9 +29,9 @@ var addon = require( './../src/addon.node' );
 * Returns the expected value (mean) of a triangular distribution.
 *
 * @private
-* @param {NonNegativeNumber} a - lower bound
-* @param {NonNegativeNumber} b - upper bound
-* @param {NonNegativeNumber} c - mode (peak)
+* @param {NonNegativeNumber} a - minimum support
+* @param {NonNegativeNumber} b - maximum support
+* @param {NonNegativeNumber} c - mode
 * @returns {NonNegativeNumber} expected value (mean)
 *
 * @example

base/dists/triangular/mode/README.md

@@ -222,7 +222,7 @@ int main( void ) {
     for ( i = 0; i < 25; i++ ) {
         a = random_uniform( 0.0, 10.0 );
         b = random_uniform( 0.0, 10.0 ) + a;
-        c = a + (b - a) * random_uniform( 0.0, 1.0 ); // mode between a and b
+        c = random_uniform( a, b ); // mode between a and b
         y = stdlib_base_dists_triangular_mode( a, b, c );
         printf( "a: %lf, b: %lf, c: %lf, M(X;a,b,c): %lf\n", a, b, c, y );
     }

base/dists/triangular/mode/benchmark/c/benchmark.c

@@ -75,13 +75,15 @@ static double tic( void ) {
 }
 
 /**
-* Generates a random number on the interval [0,20).
+* Generates a random number on the interval [min,max).
 *
-* @return random number
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
 */
-static double rand_double( void ) {
-	int r = rand();
-	return 20.0*(double)r / ( (double)RAND_MAX + 1.0 );
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
 }
 
 /**
@@ -98,9 +100,9 @@ static double benchmark( void ) {
 
 	// Generate random parameters for the triangular distribution
 	for ( i = 0; i < 100; i++ ) {
-		a[ i ] = rand_double() * 20.0;  // Lower bound
-		b[ i ] = ( rand_double() * 20.0 ) + a[ i ];  // Upper bound
-		c[ i ] = ( rand_double() * ( b[i] - a[i] ) ) + a[i];  // Mode
+		a[ i ] = random_uniform( 0.0, 20.0 ); // Lower bound
+		b[ i ] = random_uniform( a[i], 40.0 ); // Upper bound
+		c[ i ] = random_uniform( a[i], b[i] ); // Mode
 	}
 
 	t = tic();

base/dists/triangular/mode/examples/c/example.c

@@ -35,7 +35,7 @@ int main( void ) {
 	for ( i = 0; i < 25; i++ ) {
 		a = random_uniform( 0.0, 10.0 );
 		b = random_uniform( 0.0, 10.0 ) + a;
-		c = a + (b - a) * random_uniform( 0.0, 1.0 ); // mode between a and b
+		c = random_uniform( a, b ); // mode between a and b
 		y = stdlib_base_dists_triangular_mode( a, b, c );
 		printf( "a: %lf, b: %lf, c: %lf, M(X;a,b,c): %lf\n", a, b, c, y );
 	}

base/dists/triangular/mode/include/stdlib/stats/base/dists/triangular/mode.h

@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Returns the mode of a triangular distribution with lower bound `a`, upper bound `b`, and mode `c`.
+* Returns the mode of a triangular distribution.
 */
 double stdlib_base_dists_triangular_mode( const double a, const double b, const double c );
 

base/dists/triangular/mode/lib/native.js

@@ -29,10 +29,10 @@ var addon = require( './../src/addon.node' );
 * Returns the mode of a triangular distribution.
 *
 * @private
-* @param {NonNegativeNumber} a - lower bound
-* @param {NonNegativeNumber} b - upper bound
-* @param {NonNegativeNumber} c - mode (peak)
-* @returns {NonNegativeNumber} mode
+* @param {number} a - minimum support
+* @param {number} b - maximum support
+* @param {number} c - mode
+* @returns {number} mode
 *
 * @example
 * var v = mode( 0.0, 10.0, 5.0 );

base/dists/triangular/mode/src/main.c

@@ -22,13 +22,13 @@
 /**
 * Returns the mode of a triangular distribution.
 *
-* @param a  lower bound
-* @param b  upper bound
-* @param c  mode (peak)
+* @param a  minimum support
+* @param b  maximum support
+* @param c  mode
 * @returns  mode
 *
 * @example
-* var v = mode( 0.0, 10.0, 5.0 );
+* double v = mode( 0.0, 10.0, 5.0 );
 * // returns 5.0
 */
 double stdlib_base_dists_triangular_mode( const double a, const double b, const double c ) {