chore: minor clean-up

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: passed
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: passed
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: passed
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: passed
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

Author: Planeshifter

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

@@ -170,7 +170,7 @@ for ( i = 0; i < 10; i++ ) {
 
 #### stdlib_base_dists_logistic_pdf( x, mu, s )
 
-Returns the pdf for a logistic distribution with input `x`, location `mu` and scale `s`.
+Evaluates the [probability density function][pdf] (PDF) for a [logistic][logistic-distribution] distribution with parameters `mu` (location parameter) and `s` (scale parameter).
 
 ```c
 double out = stdlib_base_dists_logistic_pdf( 2.0, 0.0, 1.0 );
@@ -188,34 +188,46 @@ double stdlib_base_dists_logistic_pdf( const double x, const double mu, const do
 ```
 
 </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/logistic/pdf.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 mu;
     double s;
     double x;
     double y;
     int i;
+
     for ( i = 0; i < 25; i++ ) {
-        mu = random_uniform( 0.0, 10.0 ) - 5.0;
+        mu = random_uniform( -5.0, 5.0 );
         s = random_uniform( 0.0, 20.0 );
-        x = random_uniform( 0.0, 10.0 );
+        x = random_uniform( -10.0, 10.0 );
         y = stdlib_base_dists_logistic_pdf( x, mu, s );
-        printf( "x: %lf, µ: %lf, s: %lf, Pdf(X;x,µ,s): %lf\n", x, mu, s, y );
+        printf( "x: %lf, µ: %lf, s: %lf, f(x;µ,s): %lf\n", x, mu, s, y );
     }
 }
 ```

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

@@ -24,7 +24,7 @@ var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var Float64Array = require( '@stdlib/array/float64' );
 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 EPS = require( '@stdlib/constants/float64/eps' );
 var pkg = require( './../package.json' ).name;
@@ -53,9 +53,9 @@ bench( pkg, opts, function benchmark( b ) {
 	mu = new Float64Array( len );
 	s = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		x[ i ] = ( randu()*40.0 ) - 20.0;
-		mu[ i ] = ( randu() * 100.0 ) - 50.0;
-		s[ i ] = ( randu() * 20.0 ) + EPS;
+		x[ i ] = uniform( -20.0, 20.0 );
+		mu[ i ] = uniform( -50.0, 50.0 );
+		s[ i ] = uniform( EPS, 20.0 );
 	}
 
 	b.tic();

lib/node_modules/@stdlib/stats/base/dists/logistic/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, 100.0 );
-		mu[ i ] = random_uniform( 0.0, 100.0 );
-		s[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		x[ i ] = random_uniform( -100.0, 100.0 );
+		mu[ i ] = random_uniform( -50.0, 50.0 );
+		s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 );
 	}
 
 	t = tic();

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

@@ -37,6 +37,6 @@ int main( void ) {
 		mu = random_uniform( 0.0, 10.0 );
 		s = random_uniform( 0.0, 10.0 );
 		y = stdlib_base_dists_logistic_pdf( x, mu, s );
-		printf( "x: %lf, µ: %lf, s: %lf, pdf(X;x,µ,s): %lf\n", x, mu, s, y );
+		printf( "x: %lf, µ: %lf, s: %lf, f(x;µ,s): %lf\n", x, mu, s, y );
 	}
 }

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

@@ -28,6 +28,7 @@ var addon = require( './../src/addon.node' );
 /**
 * Evaluates the probability density function (PDF) for a logistic distribution with location parameter `mu` and scale parameter `s` at a value `x`.
 *
+* @private
 * @param {number} x - input value
 * @param {number} mu - location parameter
 * @param {NonNegativeNumber} s - scale parameter

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

@@ -27,43 +27,14 @@
 /**
 * Evaluates the probability density function (PDF) for a logistic distribution with location parameter `mu` and scale parameter `s` at a value `x`.
 *
-* @param {number} x - input value
-* @param {number} mu - location parameter
-* @param {NonNegativeNumber} s - scale parameter
-* @returns {number} evaluated PDF
+* @param x    input value
+* @param mu   location parameter
+* @param s    scale parameter
+* @return     evaluated PDF
 *
 * @example
 * double y = stdlib_base_dists_logistic_pdf( 2.0, 0.0, 1.0 );
 * // returns ~0.105
-*
-* @example
-* double y = stdlib_base_dists_logistic_pdf( -1.0, 4.0, 2.0 );
-* // returns ~0.035
-*
-* @example
-* double y = stdlib_base_dists_logistic_pdf( NaN, 0.0, 1.0 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_logistic_pdf( 0.0, NaN, 1.0 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_logistic_pdf( 0.0, 0.0, NaN );
-* // returns NaN
-*
-* @example
-* // Negative scale parameter:
-* double y = stdlib_base_dists_logistic_pdf( 2.0, 0.0, -1.0 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_logistic_pdf( 2.0, 8.0, 0.0 );
-* // returns 0.0
-*
-* @example
-* double y = stdlib_base_dists_logistic_pdf( 8.0, 8.0, 0.0 );
-* // returns Infinity
 */
 double stdlib_base_dists_logistic_pdf( const double x, const double mu, const double s ) {
 	double ez;