diff --git a/lib/node_modules/@stdlib/stats/base/dists/laplace/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/laplace/ctor/benchmark/benchmark.js
index a616200f1eef..cadcbcd4e334 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/laplace/ctor/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/laplace/ctor/benchmark/benchmark.js
@@ -21,8 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var Float64Array = require( '@stdlib/array/float64' );
-var uniform = require( '@stdlib/random/base/uniform' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
 var pkg = require( './../package.json' ).name;
@@ -33,22 +32,20 @@ var Laplace = require( './../lib' );
 
 bench( pkg+'::instantiation', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var i;
 
-	len = 100;
-	mu = new Float64Array( len );
-	b = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		mu[ i ] = uniform( EPS, 10.0 );
-		b[ i ] = uniform( EPS, 10.0 );
-	}
+	opts = {
+		'dtype': 'float64'
+	};
+	mu = uniform( 100, EPS, 10.0, opts );
+	b = uniform( 100, EPS, 10.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist = new Laplace( mu[ i % len ], b[ i % len ] );
+		dist = new Laplace( mu[ i % mu.length ], b[ i % b.length ] );
 		if ( !( dist instanceof Laplace ) ) {
 			bm.fail( 'should return a distribution instance' );
 		}
@@ -89,7 +86,7 @@ bench( pkg+'::get:mu', function benchmark( bm ) {
 
 bench( pkg+'::set:mu', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var y;
@@ -97,17 +94,17 @@ bench( pkg+'::set:mu', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	y = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		y[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	y = uniform( 100, EPS, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.mu = y[ i % len ];
-		if ( dist.mu !== y[ i % len ] ) {
+		dist.mu = y[ i % y.length ];
+		if ( dist.mu !== y[ i % y.length ] ) {
 			bm.fail( 'should return set value' );
 		}
 	}
@@ -147,7 +144,7 @@ bench( pkg+'::get:b', function benchmark( bm ) {
 
 bench( pkg+'::set:b', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var y;
@@ -155,17 +152,17 @@ bench( pkg+'::set:b', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	y = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		y[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	y = uniform( 100, EPS, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.b = y[ i % len ];
-		if ( dist.b !== y[ i % len ] ) {
+		dist.b = y[ i % y.length ];
+		if ( dist.b !== y[ i % y.length ] ) {
 			bm.fail( 'should return set value' );
 		}
 	}
@@ -179,7 +176,7 @@ bench( pkg+'::set:b', function benchmark( bm ) {
 
 bench( pkg+':entropy', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -188,16 +185,16 @@ bench( pkg+':entropy', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
 	dist = new Laplace( mu, b );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.mu = x[ i % len ];
+		dist.mu = x[ i % x.length ];
 		y = dist.entropy;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -213,7 +210,7 @@ bench( pkg+':entropy', function benchmark( bm ) {
 
 bench( pkg+':kurtosis', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -222,16 +219,16 @@ bench( pkg+':kurtosis', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.mu = x[ i % len ];
+		dist.mu = x[ i % x.length ];
 		y = dist.kurtosis;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -247,7 +244,7 @@ bench( pkg+':kurtosis', function benchmark( bm ) {
 
 bench( pkg+':mean', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -256,16 +253,16 @@ bench( pkg+':mean', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.mu = x[ i % len ];
+		dist.mu = x[ i % x.length ];
 		y = dist.mean;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -281,7 +278,7 @@ bench( pkg+':mean', function benchmark( bm ) {
 
 bench( pkg+':median', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var x;
 	var b;
@@ -290,16 +287,16 @@ bench( pkg+':median', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.mu = x[ i % len ];
+		dist.mu = x[ i % x.length ];
 		y = dist.median;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -315,7 +312,7 @@ bench( pkg+':median', function benchmark( bm ) {
 
 bench( pkg+':mode', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -324,16 +321,16 @@ bench( pkg+':mode', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 1.0 + EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS + 1.0, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.mu = x[ i % len ];
+		dist.mu = x[ i % x.length ];
 		y = dist.mode;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -349,7 +346,7 @@ bench( pkg+':mode', function benchmark( bm ) {
 
 bench( pkg+':skewness', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -358,16 +355,16 @@ bench( pkg+':skewness', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.mu = x[ i % len ];
+		dist.mu = x[ i % x.length ];
 		y = dist.skewness;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -383,7 +380,7 @@ bench( pkg+':skewness', function benchmark( bm ) {
 
 bench( pkg+':stdev', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -392,16 +389,16 @@ bench( pkg+':stdev', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.mu = x[ i % len ];
+		dist.mu = x[ i % x.length ];
 		y = dist.stdev;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -417,7 +414,7 @@ bench( pkg+':stdev', function benchmark( bm ) {
 
 bench( pkg+':variance', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -426,16 +423,16 @@ bench( pkg+':variance', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( EPS, 100.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, EPS, 100.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		dist.mu = x[ i % len ];
+		dist.mu = x[ i % x.length ];
 		y = dist.variance;
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
@@ -451,7 +448,7 @@ bench( pkg+':variance', function benchmark( bm ) {
 
 bench( pkg+':cdf', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -460,16 +457,16 @@ bench( pkg+':cdf', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
 	dist = new Laplace( mu, b );
-	x = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( -3.0, 3.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, -3.0, 3.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		y = dist.cdf( x[ i % len ] );
+		y = dist.cdf( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
 		}
@@ -484,7 +481,7 @@ bench( pkg+':cdf', function benchmark( bm ) {
 
 bench( pkg+':logcdf', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -493,16 +490,16 @@ bench( pkg+':logcdf', function benchmark( bm ) {
 
 	mu = 1.0;
 	b = 2.0;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	len = 100;
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( -3.0, 3.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, -3.0, 3.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		y = dist.logcdf( x[ i % len ] );
+		y = dist.logcdf( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
 		}
@@ -517,7 +514,7 @@ bench( pkg+':logcdf', function benchmark( bm ) {
 
 bench( pkg+':logpdf', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -526,16 +523,16 @@ bench( pkg+':logpdf', function benchmark( bm ) {
 
 	mu = 1.0;
 	b = 2.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( -3.0, 3.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, -3.0, 3.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		y = dist.logpdf( x[ i % len ] );
+		y = dist.logpdf( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
 		}
@@ -550,7 +547,7 @@ bench( pkg+':logpdf', function benchmark( bm ) {
 
 bench( pkg+':mgf', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -559,16 +556,16 @@ bench( pkg+':mgf', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 0.2;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 0.0, 1.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, 0.0, 1.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		y = dist.mgf( x[ i % len ] );
+		y = dist.mgf( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
 		}
@@ -583,7 +580,7 @@ bench( pkg+':mgf', function benchmark( bm ) {
 
 bench( pkg+':pdf', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -592,16 +589,16 @@ bench( pkg+':pdf', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( -3.0, 3.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, -3.0, 3.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		y = dist.pdf( x[ i % len ] );
+		y = dist.pdf( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
 		}
@@ -616,7 +613,7 @@ bench( pkg+':pdf', function benchmark( bm ) {
 
 bench( pkg+':quantile', function benchmark( bm ) {
 	var dist;
-	var len;
+	var opts;
 	var mu;
 	var b;
 	var x;
@@ -625,16 +622,16 @@ bench( pkg+':quantile', function benchmark( bm ) {
 
 	mu = 2.0;
 	b = 3.0;
-	len = 100;
-	x = new Float64Array( len );
 	dist = new Laplace( mu, b );
-	for ( i = 0; i < len; i++ ) {
-		x[ i ] = uniform( 0.0, 1.0 );
-	}
+
+	opts = {
+		'dtype': 'float64'
+	};
+	x = uniform( 100, 0.0, 1.0, opts );
 
 	bm.tic();
 	for ( i = 0; i < bm.iterations; i++ ) {
-		y = dist.quantile( x[ i % len ] );
+		y = dist.quantile( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			bm.fail( 'should not return NaN' );
 		}