feat: update stats/strided/distances TypeScript declarations

PR-URL: stdlib-js#9936
Reviewed-by: Athan Reines <kgryte@gmail.com>

Author: stdlib-bot

lib/node_modules/@stdlib/stats/strided/distances/docs/types/index.d.ts

@@ -20,16 +20,196 @@
 
 /* eslint-disable max-lines */
 
+import dchebychev = require( '@stdlib/stats/strided/distances/dchebychev' );
 import dcityblock = require( '@stdlib/stats/strided/distances/dcityblock' );
+import dcosineDistance = require( '@stdlib/stats/strided/distances/dcosine-distance' );
+import dcosineSimilarity = require( '@stdlib/stats/strided/distances/dcosine-similarity' );
+import deuclidean = require( '@stdlib/stats/strided/distances/deuclidean' );
+import dsquaredEuclidean = require( '@stdlib/stats/strided/distances/dsquared-euclidean' );
 
 /**
-* Interface describing a namespace.
+* Interface describing the `distances` namespace.
 */
 interface Namespace {
 	/**
-	* TODO
+	* Computes the Chebychev distance between two double-precision floating-point strided arrays.
+	*
+	* @param N - number of indexed elements
+	* @param x - first input array
+	* @param strideX - `x` stride length
+	* @param y - second input array
+	* @param strideY - `y` stride length
+	* @returns Chebychev distance
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+	* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+	*
+	* var z = ns.dchebychev( x.length, x, 1, y, 1 );
+	* // returns 9.0
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+	* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+	*
+	* var z = ns.dchebychev.ndarray( x.length, x, 1, 0, y, 1, 0 );
+	* // returns 9.0
+	*/
+	dchebychev: typeof dchebychev;
+
+	/**
+	* Computes the city block (Manhattan) distance between two double-precision floating-point strided arrays.
+	*
+	* @param N - number of indexed elements
+	* @param x - first input array
+	* @param strideX - `x` stride length
+	* @param y - second input array
+	* @param strideY - `y` stride length
+	* @returns city block (Manhattan) distance
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+	* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+	*
+	* var z = ns.dcityblock( x.length, x, 1, y, 1 );
+	* // returns 26.0
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+	* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+	*
+	* var z = ns.dcityblock.ndarray( x.length, x, 1, 0, y, 1, 0 );
+	* // returns 26.0
 	*/
 	dcityblock: typeof dcityblock;
+
+	/**
+	* Computes the cosine distance between two double-precision floating-point strided arrays.
+	*
+	* @param N - number of indexed elements
+	* @param x - first input array
+	* @param strideX - `x` stride length
+	* @param y - second input array
+	* @param strideY - `y` stride length
+	* @returns cosine distance
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+	* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+	*
+	* var z = ns.dcosineDistance( x.length, x, 1, y, 1 );
+	* // returns ~1.061
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+	* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+	*
+	* var z = ns.dcosineDistance.ndarray( x.length, x, 1, 0, y, 1, 0 );
+	* // returns ~1.061
+	*/
+	dcosineDistance: typeof dcosineDistance;
+
+	/**
+	* Computes the cosine similarity of two double-precision floating-point strided arrays.
+	*
+	* @param N - number of indexed elements
+	* @param x - first input array
+	* @param strideX - `x` stride length
+	* @param y - second input array
+	* @param strideY - `y` stride length
+	* @returns cosine similarity
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+	* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+	*
+	* var z = ns.dcosineSimilarity( x.length, x, 1, y, 1 );
+	* // returns ~-0.061
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+	* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+	*
+	* var z = ns.dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, 0 );
+	* // returns ~-0.061
+	*/
+	dcosineSimilarity: typeof dcosineSimilarity;
+
+	/**
+	* Computes the Euclidean distance between two double-precision floating-point strided arrays.
+	*
+	* @param N - number of indexed elements
+	* @param x - first input array
+	* @param strideX - `x` stride length
+	* @param y - second input array
+	* @param strideY - `y` stride length
+	* @returns Euclidean distance
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+	* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+	*
+	* var z = ns.deuclidean( x.length, x, 1, y, 1 );
+	* // returns ~8.485
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+	* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+	*
+	* var z = ns.deuclidean.ndarray( x.length, x, 1, 0, y, 1, 0 );
+	* // returns ~8.485
+	*/
+	deuclidean: typeof deuclidean;
+
+	/**
+	* Computes the squared Euclidean distance between two double-precision floating-point strided arrays.
+	*
+	* @param N - number of indexed elements
+	* @param x - first input array
+	* @param strideX - `x` stride length
+	* @param y - second input array
+	* @param strideY - `y` stride length
+	* @returns squared Euclidean distance
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+	* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+	*
+	* var z = ns.dsquaredEuclidean( x.length, x, 1, y, 1 );
+	* // returns 72.0
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+	* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+	*
+	* var z = ns.dsquaredEuclidean.ndarray( x.length, x, 1, 0, y, 1, 0 );
+	* // returns 72.0
+	*/
+	dsquaredEuclidean: typeof dsquaredEuclidean;
 }
 
 /**