chore: clean-up and fix test tolerances

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---

Author: kgryte

lib/node_modules/@stdlib/stats/base/dists/weibull/entropy/README.md

@@ -217,8 +217,8 @@ static double random_uniform( const double min, const double max ) {
 }
 
 int main( void ) {
-    double k;
     double lambda;
+    double k;
     double y;
     int i;
 

lib/node_modules/@stdlib/stats/base/dists/weibull/entropy/src/addon.c

@@ -19,5 +19,4 @@
 #include "stdlib/stats/base/dists/weibull/entropy.h"
 #include "stdlib/math/base/napi/binary.h"
 
-// cppcheck-suppress shadowFunction
 STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_weibull_entropy )

lib/node_modules/@stdlib/stats/base/dists/weibull/entropy/test/test.js

@@ -25,6 +25,7 @@ var abs = require( '@stdlib/math/base/special/abs' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
 var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
 var entropy = require( './../lib' );
 
 
@@ -111,7 +112,7 @@ tape( 'the function returns the differential entropy of a Weibull distribution',
 			t.equal( y, expected[i], 'k: '+k[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
 		} else {
 			delta = abs( y - expected[ i ] );
-			tol = 1e-11 * abs( expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
 			t.ok( delta <= tol, 'within tolerance. k: '+k[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
 		}
 	}

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

@@ -27,6 +27,7 @@ var abs = require( '@stdlib/math/base/special/abs' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
 var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
 
 
 // VARIABLES //
@@ -120,7 +121,7 @@ tape( 'the function returns the differential entropy of a Weibull distribution',
 			t.equal( y, expected[i], 'k: '+k[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
 		} else {
 			delta = abs( y - expected[ i ] );
-			tol = 1e-11 * abs( expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
 			t.ok( delta <= tol, 'within tolerance. k: '+k[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
 		}
 	}