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/weibull/mgf/README.md

@@ -188,7 +188,7 @@ for ( i = 0; i < 10; i++ ) {
 
 #### stdlib_base_dists_weibull_mgf( t, k, lambda )
 
-Evaluates the mgf for an weibull distribution.
+Evaluates the [moment-generating function][mgf] (MGF) for a [Weibull][weibull-distribution] distribution with [shape parameter][shape] `k` and [scale parameter][scale] `lambda`.
 
 ```c
 double out = stdlib_base_dists_weibull_mgf( 1.0, 1.0, 0.5 );
@@ -197,7 +197,7 @@ double out = stdlib_base_dists_weibull_mgf( 1.0, 1.0, 0.5 );
 
 The function accepts the following arguments:
 
--   **t**: `[in] double` shape parameter.
+-   **t**: `[in] double` input value.
 -   **k**: `[in] double` shape parameter.
 -   **λ**: `[in] double` scale parameter.
 
@@ -206,35 +206,47 @@ double stdlib_base_dists_weibull_mgf( const double t, const double k, const doub
 ```
 
 </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/weibull/mgf.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 lambda;
     double k;
     double t;
     double y;
     int i;
+
     for ( i = 0; i < 25; i++ ) {
-        t = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
-        k = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
-        lambda = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+        t = random_uniform( 0.0, 5.0 );
+        k = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
+        lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
         y = stdlib_base_dists_weibull_mgf( t, k, lambda );
-        printf( "t: %lf, k: %lf, λ: %lf, E(X;k,λ): %lf\n", t, k, lambda, y );
+        printf( "t: %lf, k: %lf, λ: %lf, M_X(t;k,λ): %lf\n", t, k, lambda, y );
     }
 }
 ```

lib/node_modules/@stdlib/stats/base/dists/weibull/mgf/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 ) {
 	t = new Float64Array( len );
 	lambda = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		t[ i ] = ( randu() * 10.0 ) + EPS;
-		k[ i ] = ( randu() * 10.0 ) + EPS;
-		lambda[ i ] = ( randu() * 10.0 ) + EPS;
+		t[ i ] = uniform( 0.0, 5.0 );
+		k[ i ] = uniform( EPS, 10.0 );
+		lambda[ i ] = uniform( EPS, 10.0 );
 	}
 
 	b.tic();

lib/node_modules/@stdlib/stats/base/dists/weibull/mgf/benchmark/c/benchmark.c

@@ -102,9 +102,9 @@ static double benchmark( void ) {
 	int i;
 
 	for ( i = 0; i < 100; i++ ) {
-		lambda[ i ] = random_uniform( 0.0, 1.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
-		k[ i ] = random_uniform( 0.0, 1.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
-		s[ i ] = random_uniform( 0.0, 1.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
+		k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
+		s[ i ] = random_uniform( 0.0, 5.0 );
 	}
 
 	t = tic();

lib/node_modules/@stdlib/stats/base/dists/weibull/mgf/examples/c/example.c

@@ -34,10 +34,10 @@ int main( void ) {
 	int i;
 
 	for ( i = 0; i < 25; i++ ) {
-		t = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
-		k = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
-		lambda = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		t = random_uniform( 0.0, 5.0 );
+		k = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
+		lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
 		y = stdlib_base_dists_weibull_mgf( t, k, lambda );
-		printf( "t: %lf, k: %lf, λ: %lf, MGF(X;t,k,λ): %lf\n", t, k, lambda, y );
+		printf( "t: %lf, k: %lf, λ: %lf, M_X(t;k,λ): %lf\n", t, k, lambda, y );
 	}
 }

lib/node_modules/@stdlib/stats/base/dists/weibull/mgf/include/stdlib/stats/base/dists/weibull/mgf.h

@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Returns the mgf of an weibull distribution.
+* Evaluates the mgf of a Weibull distribution.
 */
 double stdlib_base_dists_weibull_mgf( const double t, const double k, const double lambda );
 

lib/node_modules/@stdlib/stats/base/dists/weibull/mgf/lib/native.js

@@ -28,6 +28,7 @@ var addon = require( './../src/addon.node' );
 /**
 * Evaluates the moment-generating function (MGF) for a Weibull distribution with shape `k` and scale `lambda` at a value `t`.
 *
+* @private
 * @param {number} t - input value
 * @param {PositiveNumber} k - shape parameter
 * @param {PositiveNumber} lambda - scale parameter

lib/node_modules/@stdlib/stats/base/dists/weibull/mgf/src/main.c

@@ -26,46 +26,14 @@
 /**
 * Evaluates the moment-generating function (MGF) for a Weibull distribution with shape `k` and scale `lambda` at a value `t`.
 *
-* @param {number} t - input value
-* @param {PositiveNumber} k - shape parameter
-* @param {PositiveNumber} lambda - scale parameter
-* @returns {number} evaluated MGF
+* @param t       input value
+* @param k       shape parameter
+* @param lambda  scale parameter
+* @return        evaluated MGF
 *
 * @example
 * double y = stdlib_base_dists_weibull_mgf( 1.0, 1.0, 0.5 );
 * // returns ~2.0
-*
-* @example
-* double y = stdlib_base_dists_weibull_mgf( -1.0, 4.0, 4.0 );
-* // returns ~0.019
-*
-* @example
-* double y = stdlib_base_dists_weibull_mgf( NaN, 1.0, 1.0 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_weibull_mgf( 0.0, NaN, 1.0 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_weibull_mgf( 0.0, 1.0, NaN );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_weibull_mgf( 0.2, -1.0, 0.5 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_weibull_mgf( 0.2, 0.0, 0.5 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_weibull_mgf( 0.2, 0.5, -1.0 );
-* // returns NaN
-*
-* @example
-* double y = stdlib_base_dists_weibull_mgf( 0.2, 0.5, 0.0 );
-* // returns NaN
 */
 double stdlib_base_dists_weibull_mgf( const double t, const double k, const double lambda ) {
 	double summand;
@@ -79,7 +47,7 @@ double stdlib_base_dists_weibull_mgf( const double t, const double k, const doub
 		stdlib_base_is_nan( lambda ) ||
 		k <= 0.0 ||
 		lambda <= 0.0
-	 ) {
+	) {
 		return 0.0 / 0.0; // NaN
 	}
 	sum = 1.0;