chore: minor clean-up

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---

Author: Planeshifter

lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/README.md

@@ -145,6 +145,105 @@ 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/invgamma/pdf.h"
+```
+
+#### stdlib_base_dists_invgamma_pdf( x, alpha, beta )
+
+Evaluates the [probability density function][pdf] (PDF) for an [inverse gamma][inverse-gamma]  distribution with parameters `alpha` (shape parameter) and `beta` (rate parameter).
+
+```c
+double out = stdlib_base_dists_invgamma_pdf( 2.0, 0.5, 1.0 );
+// returns ~0.121
+```
+
+The function accepts the following arguments:
+
+-   **x**: `[in] double` input value.
+-   **alpha**: `[in] double` shape parameter.
+-   **beta**: `[in] double` rate parameter.
+
+```c
+double stdlib_base_dists_invgamma_pdf( const double x, const double alpha, const double beta );
+```
+
+</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/invgamma/pdf.h"
+#include "stdlib/constants/float64/eps.h"
+#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 alpha;
+    double beta;
+    double x;
+    double y;
+    int i;
+
+    for ( i = 0; i < 25; i++ ) {
+        x = random_uniform( 0.0, 2.0 );
+        alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 5.0 );
+        beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 5.0 );
+        y = stdlib_base_dists_invgamma_pdf( x, alpha, beta );
+        printf( "x: %lf, α: %lf, β: %lf, f(x;α,β): %lf\n", x, alpha, beta, 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/invgamma/pdf/benchmark/benchmark.native.js

@@ -23,7 +23,7 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var tryRequire = require( '@stdlib/utils/try-require' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var Float64Array = require( '@stdlib/array/float64' );
 var EPS = require( '@stdlib/constants/float64/eps' );
@@ -53,9 +53,9 @@ bench( pkg, opts, function benchmark( b ) {
 	beta = new Float64Array( len );
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		alpha[ i ] = ( randu()*10.0 ) + 4.0 + EPS;
-		beta[ i ] = ( randu()*10.0 ) + EPS;
-		x[ i ] = ( randu()*10.0 ) + EPS;
+		alpha[ i ] = uniform( EPS, 10.0 );
+		beta[ i ] = uniform( EPS, 10.0 );
+		x[ i ] = uniform( EPS, 10.0 );
 	}
 
 	b.tic();

lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/benchmark/c/benchmark.c

@@ -102,9 +102,9 @@ static double benchmark( void ) {
 	int i;
 
 	for ( i = 0; i < 100; i++ ) {
-		x[ i ] = random_uniform( 0.0, 10.0 ) + 4.0 + STDLIB_CONSTANT_FLOAT64_EPS;
-		alpha[ i ] = random_uniform( 0.0, 10.0 ) + 4.0 + STDLIB_CONSTANT_FLOAT64_EPS;
-		beta[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		x[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
+		alpha[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
+		beta[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
 	}
 
 	t = tic();

lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/examples/c/example.c

@@ -34,10 +34,10 @@ int main( void ) {
 	int i;
 
 	for ( i = 0; i < 25; i++ ) {
-		alpha = random_uniform( 0.0, 5.0 );
-		beta = random_uniform( 0.0, 5.0 );
 		x = random_uniform( 0.0, 2.0 );
+		alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 5.0 );
+		beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 5.0 );
 		y = stdlib_base_dists_invgamma_pdf( x, alpha, beta );
-		printf( "x: %lf, α: %lf, β: %lf, Pdf(X;x,α,β): %lf\n", x, alpha, beta, y );
+		printf( "x: %lf, α: %lf, β: %lf, f(x;α,β): %lf\n", x, alpha, beta, y );
 	}
 }

lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/include/stdlib/stats/base/dists/invgamma/pdf.h

@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Returns the probability density function (PDF) for an inverse gamma distribution with shape parameter `alpha` and scale parameter `beta` at a value `x`.
+* Evaluates the probability density function (PDF) for an inverse gamma distribution.
 */
 double stdlib_base_dists_invgamma_pdf( const double x, const double alpha, const double beta );
 

lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/lib/native.js

@@ -28,6 +28,7 @@ var addon = require( './../src/addon.node' );
 /**
 * Evaluates the probability density function (PDF) for an inverse gamma distribution with shape parameter `alpha` and scale parameter `beta` at a value `x`.
 *
+* @private
 * @param {number} x - input value
 * @param {PositiveNumber} alpha - shape parameter
 * @param {PositiveNumber} beta - scale parameter

lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/src/main.c

@@ -23,46 +23,16 @@
 #include "stdlib/math/base/special/ln.h"
 
 /**
-* Returns the probability density function (PDF) for an inverse gamma distribution with shape parameter `alpha` and scale parameter `beta` at a value `x`.
+* Evaluates the probability density function (PDF) for an inverse gamma distribution with shape parameter `alpha` and scale parameter `beta` at a value `x`.
 *
-* @param {number} x - input value
-* @param {PositiveNumber} alpha - shape parameter
-* @param {PositiveNumber} beta - scale parameter
-* @returns {number} evaluated PDF
+* @param x     input value
+* @param alpha shape parameter
+* @param beta  scale parameter
+* @return      evaluated PDF
 *
 * @example
 * double y = stdlib_base_dists_invgamma_pdf( 2.0, 0.5, 1.0 );
 * // returns ~0.121
-*
-* @example
-* double y = stdlib_base_dists_invgamma_pdf( 0.2, 1.0, 1.0 );
-* // returns ~0.168
-*
-* @example
-* double y = stdlib_base_dists_invgamma_pdf( -1.0, 4.0, 2.0 );
-* // returns 0.0
-*
-* @example
-* double y = stdlib_base_dists_invgamma_pdf( NaN, 1.0, 1.0 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_invgamma_pdf( 0.0, NaN, 1.0 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_invgamma_pdf( 0.0, 1.0, NaN );
-* // returns NaN
-*
-* @example
-* // Negative shape parameter:
-* double y = stdlib_base_dists_invgamma_pdf( 2.0, -1.0, 1.0 );
-* // returns NaN
-*
-* @example
-* // Negative scale parameter:
-* double y = stdlib_base_dists_invgamma_pdf( 2.0, 1.0, -1.0 );
-* // returns NaN
 */
 double stdlib_base_dists_invgamma_pdf( const double x, const double alpha, const double beta ) {
 	double lnl;