issue#1632 resolved

stdlib-js · Jul 15, 2024 · 2786956 · 2786956
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diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/README.md b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/README.md
@@ -111,6 +111,76 @@ var objectKeys = require( '@stdlib/utils/keys' );
 var kumaraswamy = require( '@stdlib/stats/base/dists/kumaraswamy' );
 
 console.log( objectKeys( kumaraswamy ) );
+// Create a Kumaraswamy distribution object
+var a = 2.0;
+var b = 5.0;
+var dist = new kumaraswamy.Kumaraswamy( a, b );
+
+// Calculate basic distribution properties
+console.log( 'Mean: %d', dist.mean );
+console.log( 'Median: %d', dist.median );
+console.log( 'Mode: %d', dist.mode );
+console.log( 'Variance: %d', dist.variance );
+
+// Evaluate the probability density function (PDF)
+var x = 0.5;
+var y = dist.pdf( x );
+console.log( 'PDF at x = %d: %d', x, y );
+
+// Evaluate the cumulative distribution function (CDF)
+y = dist.cdf( x );
+console.log( 'CDF at x = %d: %d', x, y );
+
+// Evaluate the natural logarithm of PDF and CDF
+console.log( 'Log PDF at x = %d: %d', x, dist.logpdf( x ) );
+console.log( 'Log CDF at x = %d: %d', x, dist.logcdf( x ) );
+
+// Calculate the quantile for a given probability
+var p = 0.75;
+x = dist.quantile( p );
+console.log( 'Quantile at p = %d: %d', p, x );
+
+// Generate random numbers
+var r = new Array( 5 );
+for ( var i = 0; i < 5; i++ ) {
+    r[ i ] = kumaraswamy.random( a, b );
+}
+console.log( 'Random samples: %s', r.join( ', ' ) );
+
+// Use standalone functions
+x = 0.3;
+y = kumaraswamy.pdf( x, a, b );
+console.log( 'Standalone PDF at x = %d: %d', x, y );
+
+y = kumaraswamy.cdf( x, a, b );
+console.log( 'Standalone CDF at x = %d: %d', x, y );
+
+y = kumaraswamy.quantile( 0.9, a, b );
+console.log( 'Standalone Quantile at p = 0.9: %d', y );
+
+// Calculate additional distribution properties
+console.log( 'Kurtosis: %d', kumaraswamy.kurtosis( a, b ) );
+console.log( 'Skewness: %d', kumaraswamy.skewness( a, b ) );
+console.log( 'Standard Deviation: %d', kumaraswamy.stdev( a, b ) );
+
+// Demonstrate the effect of different shape parameters
+console.log( '\nEffect of shape parameters:' );
+var shapes = [
+    [0.5, 0.5],
+    [5.0, 1.0],
+    [1.0, 5.0],
+    [2.0, 2.0],
+    [10.0, 10.0]
+];
+
+for ( var i = 0; i < shapes.length; i++ ) {
+    var params = shapes[i];
+    console.log( '\na = %d, b = %d', params[0], params[1] );
+    console.log( 'Mean: %d', kumaraswamy.mean( params[0], params[1] ) );
+    console.log( 'Median: %d', kumaraswamy.median( params[0], params[1] ) );
+    console.log( 'Mode: %d', kumaraswamy.mode( params[0], params[1] ) );
+    console.log( 'Skewness: %d', kumaraswamy.skewness( params[0], params[1] ) );
+}
 ```
 
 </section>

diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/examples/index.js
@@ -22,3 +22,72 @@ var objectKeys = require( '@stdlib/utils/keys' );
 var kumaraswamy = require( './../lib' );
 
 console.log( objectKeys( kumaraswamy ) );
+// Create a Kumaraswamy distribution object
+var a = 2.0;
+var b = 5.0;
+var dist = new kumaraswamy.Kumaraswamy( a, b );
+
+// Calculate basic distribution properties
+console.log( 'Mean: %d', dist.mean );
+console.log( 'Median: %d', dist.median );
+console.log( 'Mode: %d', dist.mode );
+console.log( 'Variance: %d', dist.variance );
+
+// Evaluate the probability density function (PDF)
+var x = 0.5;
+var y = dist.pdf( x );
+console.log( 'PDF at x = %d: %d', x, y );
+
+// Evaluate the cumulative distribution function (CDF)
+y = dist.cdf( x );
+console.log( 'CDF at x = %d: %d', x, y );
+
+// Evaluate the natural logarithm of PDF and CDF
+console.log( 'Log PDF at x = %d: %d', x, dist.logpdf( x ) );
+console.log( 'Log CDF at x = %d: %d', x, dist.logcdf( x ) );
+
+// Calculate the quantile for a given probability
+var p = 0.75;
+x = dist.quantile( p );
+console.log( 'Quantile at p = %d: %d', p, x );
+
+// Generate random numbers
+var r = new Array( 5 );
+for ( var i = 0; i < 5; i++ ) {
+    r[ i ] = kumaraswamy.random( a, b );
+}
+console.log( 'Random samples: %s', r.join( ', ' ) );
+
+// Use standalone functions
+x = 0.3;
+y = kumaraswamy.pdf( x, a, b );
+console.log( 'Standalone PDF at x = %d: %d', x, y );
+
+y = kumaraswamy.cdf( x, a, b );
+console.log( 'Standalone CDF at x = %d: %d', x, y );
+
+y = kumaraswamy.quantile( 0.9, a, b );
+console.log( 'Standalone Quantile at p = 0.9: %d', y );
+
+// Calculate additional distribution properties
+console.log( 'Kurtosis: %d', kumaraswamy.kurtosis( a, b ) );
+console.log( 'Skewness: %d', kumaraswamy.skewness( a, b ) );
+console.log( 'Standard Deviation: %d', kumaraswamy.stdev( a, b ) );
+
+// Demonstrate the effect of different shape parameters
+console.log( '\nEffect of shape parameters:' );
+var shapes = [
+    [0.5, 0.5],
+    [5.0, 1.0],
+    [1.0, 5.0],
+    [2.0, 2.0],
+    [10.0, 10.0]
+];
+for ( var i = 0; i < shapes.length; i++ ) {
+    var params = shapes[i];
+    console.log( '\na = %d, b = %d', params[0], params[1] );
+    console.log( 'Mean: %d', kumaraswamy.mean( params[0], params[1] ) );
+    console.log( 'Median: %d', kumaraswamy.median( params[0], params[1] ) );
+    console.log( 'Mode: %d', kumaraswamy.mode( params[0], params[1] ) );
+    console.log( 'Skewness: %d', kumaraswamy.skewness( params[0], params[1] ) );
+}