chore: minor clean-up

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
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    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: passed
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  - task: lint_javascript_src
    status: passed
  - task: lint_javascript_cli
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  - 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
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  - task: lint_typescript_tests
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  - task: lint_license_headers
    status: passed
---

Author: Planeshifter

lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/test/test.js

@@ -22,10 +22,8 @@
 
 var tape = require( 'tape' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var abs = require( '@stdlib/math/base/special/abs' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
 var NINF = require( '@stdlib/constants/float64/ninf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 var mode = require( './../lib' );
 
 
@@ -79,9 +77,7 @@ tape( 'if provided a nonpositive `beta`, the function returns `NaN`', function t
 
 tape( 'the function returns the mode of a Gumbel distribution', function test( t ) {
 	var expected;
-	var delta;
 	var beta;
-	var tol;
 	var mu;
 	var y;
 	var i;
@@ -92,13 +88,7 @@ tape( 'the function returns the mode of a Gumbel distribution', function test( t
 	for ( i = 0; i < mu.length; i++ ) {
 		y = mode( mu[i], beta[i] );
 		if ( expected[i] !== null ) {
-			if ( y === expected[i] ) {
-				t.equal( y, expected[i], 'mu:'+mu[i]+', beta: '+beta[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. mu: '+mu[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-			}
+			t.equal( y, expected[i], 'mu:'+mu[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] );
 		}
 	}
 	t.end();

lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/test/test.native.js

@@ -24,10 +24,8 @@ 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 PINF = require( '@stdlib/constants/float64/pinf' );
 var NINF = require( '@stdlib/constants/float64/ninf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 
 
 // FIXTURES //
@@ -88,9 +86,7 @@ tape( 'if provided a nonpositive `beta`, the function returns `NaN`', opts, func
 
 tape( 'the function returns the mode of a Gumbel distribution', opts, function test( t ) {
 	var expected;
-	var delta;
 	var beta;
-	var tol;
 	var mu;
 	var y;
 	var i;
@@ -101,13 +97,7 @@ tape( 'the function returns the mode of a Gumbel distribution', opts, function t
 	for ( i = 0; i < mu.length; i++ ) {
 		y = mode( mu[i], beta[i] );
 		if ( expected[i] !== null) {
-			if ( y === expected[i] ) {
-				t.equal( y, expected[i], 'mu:'+mu[i]+', beta: '+beta[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. mu: '+mu[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-			}
+			t.equal( y, expected[i], 'mu:'+mu[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] );
 		}
 	}
 	t.end();

lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/README.md

@@ -216,8 +216,7 @@ The function accepts the following arguments:
 -   **b**: `[in] double` second shape parameter.
 
 ```c
-double stdlib_base_dists_kumaraswamy_logcdf( const double x, const
-double a, const double b );
+double stdlib_base_dists_kumaraswamy_logcdf( const double x, const double a, const double b );
 ```
 
 </section>

lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/src/main.c

@@ -23,7 +23,7 @@
 #include "stdlib/constants/float64/ninf.h"
 
 /**
-* Evaluates the natural logarithm of the cumulative distribution function (CDF) for an arcsine distribution with minimum support `a` and maximum support `b` at a value `x`.
+* Evaluates the natural logarithm of the cumulative distribution function (CDF) for a Kumaraswamy's double bounded distribution with first shape parameter `a` and second shape parameter `b` at a value `x`.
 *
 * @param x    input value
 * @param a    first shape parameter

lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/README.md

@@ -102,7 +102,7 @@ y = logpdf( 1.0, 0.0, -1.0, 0.5 );
 
 #### logpdf.factory( a, b, c )
 
-Returns a function for evaluating the natural logarithm of the [probability density function][pdf] (PDF) of a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit) and `c` (mode).
+Returns a function for evaluating the natural logarithm of the [probability density function][pdf] (PDF) of a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit), and `c` (mode).
 
 ```javascript
 var mylogpdf = logpdf.factory( 0.0, 10.0, 5.0 );
@@ -190,7 +190,7 @@ for ( i = 0; i < 25; i++ ) {
 
 #### stdlib_base_dists_triangular_logpdf( x, a, b, c )
 
-Evaluates the natural logarithm of the [probability density function][pdf] (PDF) for a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit) and `c` (mode).
+Evaluates the natural logarithm of the [probability density function][pdf] (PDF) for a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit), and `c` (mode).
 
 ```c
 double y = stdlib_base_dists_triangular_logpdf( 0.5, -1.0, 1.0, 0.0 );
@@ -250,7 +250,7 @@ int main( void ) {
         x = random_uniform( 0.0, 30.0 );
         a = random_uniform( 0.0, 10.0 );
         b = random_uniform( a + STDLIB_CONSTANT_FLOAT64_EPS, 40.0 );
-        c = a + random_uniform( 0.0, b - a );
+        c = random_uniform( a, b );
         y = stdlib_base_dists_triangular_logpdf( x, a, b, c );
         printf( "x: %lf, a: %lf, b: %lf, c: %lf, ln(f(x;a,b,c)): %lf\n", x, a, b, c, y );
     }

lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/c/benchmark.c

@@ -106,7 +106,7 @@ static double benchmark( void ) {
 		x[ i ] = random_uniform( 0.0, 30.0 );
 		a[ i ] = random_uniform( 0.0, 10.0 );
 		b[ i ] = random_uniform( a[ i ] + STDLIB_CONSTANT_FLOAT64_EPS, 40.0 );
-		c[ i ] = a[ i ] + random_uniform( 0.0, b[ i ] - a[ i ] );
+		c[ i ] = random_uniform( a[ i ], b[ i ] );
 	}
 
 	t = tic();

lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/examples/c/example.c

@@ -38,8 +38,8 @@ int main( void ) {
 	for ( i = 0; i < 25; i++ ) {
 		x = random_uniform( 0.0, 30.0 );
 		a = random_uniform( 0.0, 10.0 );
-		b = random_uniform( a, 40.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
-		c = a + random_uniform( 0.0, b - a );
+		b = random_uniform( a + STDLIB_CONSTANT_FLOAT64_EPS, 40.0 );
+		c = random_uniform( a, b );
 		y = stdlib_base_dists_triangular_logpdf( x, a, b, c );
 		printf( "x: %lf, a: %lf, b: %lf, c: %lf, ln(f(x;a,b,c)): %lf\n", x, a, b, c, y );
 	}

lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/include/stdlib/stats/base/dists/triangular/logpdf.h

@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Evaluates the natural logarithm of the probability density function (PDF) for a triangular distribution with lower limit `a` and upper limit `b` and mode `c` at a value `x`.
+* Evaluates the natural logarithm of the probability density function (PDF) for a triangular distribution with lower limit `a`, upper limit `b`, and mode `c` at a value `x`.
 */
 double stdlib_base_dists_triangular_logpdf( const double x, const double a, const double b, const double c );
 

lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/lib/main.js

@@ -29,7 +29,7 @@ var LN2 = require( '@stdlib/constants/float64/ln-two' );
 // MAIN //
 
 /**
-* Evaluates the natural logarithm of the probability density function (PDF) for a triangular distribution with lower limit `a` and upper limit `b` and mode `c` at a value `x`.
+* Evaluates the natural logarithm of the probability density function (PDF) for a triangular distribution with lower limit `a`, upper limit `b`, and mode `c` at a value `x`.
 *
 * @param {number} x - input value
 * @param {number} a - lower limit

lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/lib/native.js

@@ -26,7 +26,7 @@ var addon = require( './../src/addon.node' );
 // MAIN //
 
 /**
-* Evaluates the natural logarithm of the probability density function (PDF) for a triangular distribution with lower limit `a` and upper limit `b` and mode `c` at a value `x`.
+* Evaluates the natural logarithm of the probability density function (PDF) for a triangular distribution with lower limit `a`, upper limit `b`, and mode `c` at a value `x`.
 *
 * @private
 * @param {number} x - input value