refactor: update signature

Author: gururaj1512

lib/node_modules/@stdlib/stats/strided/ztest2/README.md

@@ -46,7 +46,7 @@ Here, `μX` and `μY` are the true population means of samples `X` and `Y`, resp
 var ztest2 = require( '@stdlib/stats/strided/ztest2' );
 ```
 
-#### ztest2( N, alternative, alpha, mu, sigmax, x, strideX, sigmay, y, strideY, out )
+#### ztest2( NX, NY, alternative, alpha, diff, sigmax, sigmay, x, strideX, y, strideY, out )
 
 Computes a two-sample Z-test for a strided array.
 
@@ -57,7 +57,7 @@ var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ];
 var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
 
 var results = new Results();
-var out = ztest2( 5, 'two-sided', 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, results );
+var out = ztest2( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, 2.0, x, 1, y, 1, results );
 // returns {...}
 
 var bool = ( out === results );
@@ -66,14 +66,15 @@ var bool = ( out === results );
 
 The function has the following parameters:
 
--   **N**: number of indexed elements.
+-   **NX**: number of indexed elements in `x`.
+-   **NY**: number of indexed elements in `y`.
 -   **alternative**: [alternative hypothesis][@stdlib/stats/base/ztest/alternatives].
 -   **alpha**: significance level.
--   **mu**: mean value under the null hypothesis.
+-   **diff**: difference in means under the null hypothesis.
 -   **sigmax**: known standard deviation of `x`.
+-   **sigmay**: known standard deviation of `y`.
 -   **x**: input array.
 -   **strideX**: stride length for `x`.
--   **sigmay**: known standard deviation of `y`.
 -   **y**: input array.
 -   **strideY**: stride length for `y`.
 -   **out**: output [results object][@stdlib/stats/base/ztest/two-sample/results/float64].
@@ -87,7 +88,7 @@ var x = [ 4.0, 0.0, 4.0, 0.0, 6.0, 0.0, 6.0, 0.0, 5.0, 0.0 ];
 var y = [ 3.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0, 7.0, 0.0 ];
 
 var results = new Results();
-var out = ztest2( 5, 'two-sided', 0.05, 0.0, 1.0, x, 2, 2.0, y, 2, results );
+var out = ztest2( 5, 5, 'two-sided', 0.05, 0.0, 1.0, 2.0, x, 2, y, 2, results );
 // returns {...}
 
 var bool = ( out === results );
@@ -109,14 +110,14 @@ var y0 = new Float64Array( [ 0.0, 3.0, 3.0, 5.0, 7.0, 7.0 ] );
 var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
 var results = new Results();
-var out = ztest2( 5, 'two-sided', 0.05, 0.0, 1.0, x1, 1, 2.0, y1, 1, results );
+var out = ztest2( 5, 5, 'two-sided', 0.05, 0.0, 1.0, 2.0, x1, 1, y1, 1, results );
 // returns {...}
 
 var bool = ( out === results );
 // returns true
 ```
 
-#### ztest2.ndarray( N, alternative, alpha, mu, sigmax, x, strideX, offsetX,  sigmay, y, strideY, offsetY, out )
+#### ztest2.ndarray( NX, NY, alternative, alpha, diff, sigmax, sigmay, x, strideX, offsetX, y, strideY, offsetY, out )
 
 Computes a two-sample Z-test for a strided array using alternative indexing semantics.
 
@@ -127,7 +128,7 @@ var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ];
 var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
 
 var results = new Results();
-var out = ztest2.ndarray( x.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 0, 2.0, y, 1, 0, results );
+var out = ztest2.ndarray( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, 2.0, x, 1, 0, y, 1, 0, results );
 // returns {...}
 
 var bool = ( out === results );
@@ -148,7 +149,7 @@ var x = [ 0.0, 4.0, 0.0, 4.0, 0.0, 6.0, 0.0, 6.0, 0.0, 5.0 ];
 var y = [ 0.0, 3.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0, 7.0 ];
 
 var results = new Results();
-var out = ztest2.ndarray( 5, 'two-sided', 0.05, 0.0, 1.0, x, 2, 1, 2.0, y, 2, 1, results );
+var out = ztest2.ndarray( 5, 5, 'two-sided', 0.05, 0.0, 1.0, 2.0, x, 2, 1, y, 2, 1, results );
 // returns {...}
 
 var bool = ( out === results );
@@ -182,15 +183,15 @@ var Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
 var normal = require( '@stdlib/random/array/normal' );
 var ztest2 = require( '@stdlib/stats/strided/ztest2' );
 
-var x = normal( 1000, 0.0, 1.0, {
+var x = normal( 1000, 4.0, 2.0, {
     'dtype': 'generic'
 });
-var y = normal( 1000, 0.0, 1.0, {
+var y = normal( 800, 3.0, 2.0, {
     'dtype': 'generic'
 });
 
 var results = new Results();
-var out = ztest2( x.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 1.0, y, 1, results );
+var out = ztest2( x.length, y.length, 'two-sided', 0.05, 1.0, 2.0, 2.0, x, 1, y, 1, results );
 // returns {...}
 
 console.log( out.toString() );
@@ -222,7 +223,7 @@ console.log( out.toString() );
 
 [@stdlib/stats/base/ztest/alternatives]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ztest/alternatives
 
-[@stdlib/stats/base/ztest/one-sample/results/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ztest/one-sample/results/float64
+[@stdlib/stats/base/ztest/two-sample/results/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ztest/two-sample/results/float64
 
 [@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
 

lib/node_modules/@stdlib/stats/strided/ztest2/benchmark/benchmark.js

@@ -62,7 +62,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			out = ztest2( x.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 1.0, y, 1, results );
+			out = ztest2( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, 1.0, x, 1, y, 1, results );
 			if ( isnan( out.statistic ) ) {
 				b.fail( 'should not return NaN' );
 			}

lib/node_modules/@stdlib/stats/strided/ztest2/benchmark/benchmark.ndarray.js

@@ -24,7 +24,7 @@ var bench = require( '@stdlib/bench' );
 var normal = require( '@stdlib/random/array/normal' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Results = require( '@stdlib/stats/base/ztest/one-sample/results/float64' );
+var Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
 var pkg = require( './../package.json' ).name;
 var ztest2 = require( './../lib/ndarray.js' );
 
@@ -62,7 +62,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			out = ztest2( x.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 0, 1.0, y, 1, 0, results );
+			out = ztest2( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, 1.0, x, 1, 0, y, 1, 0, results );
 			if ( isnan( out.statistic ) ) {
 				b.fail( 'should not return NaN' );
 			}

lib/node_modules/@stdlib/stats/strided/ztest2/docs/repl.txt

@@ -1,5 +1,5 @@
 
-{{alias}}( N, alternative, alpha, mu, sigmax, x, strideX, sigmay, y, strideY, out )
+{{alias}}( NX, NY, alternative, alpha, diff, sigmax, sigmay, x, strideX, y, strideY, out )
     Computes a two-sample Z-test for a strided array.
 
     The `N` and stride parameters determine which elements in the strided array
@@ -10,34 +10,37 @@
 
     Parameters
     ----------
-    N: integer
-        Number of indexed elements.
+    NX: integer
+        Number of indexed elements in `x`.
+
+    NY: integer
+        Number of indexed elements in `y`.
 
     alternative: string
         Alternative hypothesis. Must be one of the following:
 
-        - two-sided: mean is not equal to null value.
-        - greater: mean is larger than null value.
-        - less: mean is less than null value.
+        - two-sided: `x` has same mean as `y`
+        - greater: `x` has larger mean than `y`
+        - less: `x` has smaller mean than `y`
 
     alpha: number
         Significance level.
 
-    mu: number
-        Value of the mean under the null hypothesis.
+    diff: number
+        Difference in means under the null hypothesis.
 
     sigmax: number
         Known standard deviation of `x`.
 
+    sigmay: number
+        Known standard deviation of `y`.
+
     x: Array|TypedArray|Object
         Input array.
 
     strideX: integer
         Stride length for `x`.
 
-    sigmay: number
-        Known standard deviation of `y`.
-
     y: Array|TypedArray|Object
         Input array.
 
@@ -56,14 +59,15 @@
     --------
     > var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ];
     > var x = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
-    > var N = x.length;
+    > var NX = x.length;
+    > var NY = y.length;
     > var alt = 'two-sided';
     > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}();
-    > var res = {{alias}}( N, alt, 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, out );
+    > var res = {{alias}}( NX, NY, alt, 0.05, 0.0, 1.0, 2.0, x, 1, y, 1, out );
     > res.toString()
 
 
-{{alias}}.ndarray( N, alternative, alpha, mu, sigmax, x, strideX, offsetX, sigmay, y, strideY, offsetY, out )
+{{alias}}.ndarray( NX, NY, alternative, alpha, diff, sigmax, sigmay, x, strideX, offsetX, y, strideY, offsetY, out )
     Computes a two-sample Z-test for a strided array using alternative indexing
     semantics.
 
@@ -73,25 +77,31 @@
 
     Parameters
     ----------
-    N: integer
-        Number of indexed elements.
+    NX: integer
+        Number of indexed elements in `x`.
+
+    NY: integer
+        Number of indexed elements in `y`.
 
     alternative: string
         Alternative hypothesis. Must be one of the following:
 
-        - two-sided: mean is not equal to null value.
-        - greater: mean is larger than null value.
-        - less: mean is less than null value.
+        - two-sided: `x` has same mean as `y`
+        - greater: `x` has larger mean than `y`
+        - less: `x` has smaller mean than `y`
 
     alpha: number
         Significance level.
 
-    mu: number
-        Value of the mean under the null hypothesis.
+    diff: number
+        Difference in means under the null hypothesis.
 
     sigmax: number
         Known standard deviation of `x`.
 
+    sigmay: number
+        Known standard deviation of `y`.
+
     x: Array|TypedArray|Object
         Input array.
 
@@ -101,9 +111,6 @@
     offsetX: integer
         Starting index for `x`.
 
-    sigmay: number
-        Known standard deviation of `y`.
-
     y: Array|TypedArray|Object
         Input array.
 
@@ -125,10 +132,11 @@
     --------
     > var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ];
     > var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
-    > var N = x.length;
+    > var NX = x.length;
+    > var NY = y.length;
     > var alt = 'two-sided';
     > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}();
-    > var res = {{alias}}.ndarray( N, alt, 0.05, 0.0, 1.0, x, 1, 0, 2.0, y, 1, 0, out );
+    > var res = {{alias}}.ndarray( NX, NY, alt, 0.05, 0.0, 1.0, 2.0, x, 1, 0, y, 1, 0, out );
     > res.toString()
 
     See Also

lib/node_modules/@stdlib/stats/strided/ztest2/docs/types/index.d.ts

@@ -96,7 +96,7 @@ interface BaseResults {
 	ci: Float64Array;
 
 	/**
-	* Value of the mean under the null hypothesis
+	* Difference in means under the null hypothesis
 	*/
 	nullValue: number;
 
@@ -133,14 +133,15 @@ interface Routine {
 	/**
 	* Computes a two-sample Z-test for a strided array.
 	*
-	* @param N - number of indexed elements
+	* @param NX - number of indexed elements in `x`
+	* @param NY - number of indexed elements in `y`
 	* @param alternative - alternative hypothesis
 	* @param alpha - significance level
-	* @param mu - mean under the null hypothesis
+	* @param diff - difference in means under the null hypothesis
 	* @param sigmax - known standard deviation of `x`
+	* @param sigmay - known standard deviation of `y`
 	* @param x - input array
 	* @param strideX - stride length for `x`
-	* @param sigmay - known standard deviation of `y`
 	* @param y - input array
 	* @param strideY - stride length for `y`
 	* @param out - output results object
@@ -153,26 +154,27 @@ interface Routine {
 	* var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
 	*
 	* var results = new Results();
-	* var out = ztest2( x.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, results );
+	* var out = ztest2( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, 2.0, x, 1, y, 1, results );
 	* // returns {...}
 	*
 	* var bool = ( out === results );
 	* // returns true
 	*/
-	<T extends BaseResults>( N: number, alternative: Alternative, alpha: number, mu: number, sigmax: number, x: InputArray, strideX: number, sigmay: number, y: InputArray, strideY: number, out: T ): Results;
+	<T extends BaseResults>( NX: number, NY: number, alternative: Alternative, alpha: number, diff: number, sigmax: number, sigmay: number, x: InputArray, strideX: number, y: InputArray, strideY: number, out: T ): Results;
 
 	/**
 	* Computes a two-sample Z-test for a strided array using alternative indexing semantics.
 	*
-	* @param N - number of indexed elements
+	* @param NX - number of indexed elements in `x`
+	* @param NY - number of indexed elements in `y`
 	* @param alternative - alternative hypothesis
 	* @param alpha - significance level
-	* @param mu - mean under the null hypothesis
+	* @param diff - difference in means under the null hypothesis
 	* @param sigmax - known standard deviation of `x`
+	* @param sigmay - known standard deviation of `y`
 	* @param x - input array
 	* @param strideX - stride length for `x`
 	* @param offsetX - starting index for `x`
-	* @param sigmay - known standard deviation of `y`
 	* @param y - input array
 	* @param strideY - stride length for `y`
 	* @param offsetY - starting index for `y`
@@ -186,26 +188,27 @@ interface Routine {
 	* var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
 	*
 	* var results = new Results();
-	* var out = ztest2.ndarray( x.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 0, 2.0, y, 1, 0, results );
+	* var out = ztest2.ndarray( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, 2.0, x, 1, 0, y, 1, 0, results );
 	* // returns {...}
 	*
 	* var bool = ( out === results );
 	* // returns true
 	*/
-	ndarray<T extends BaseResults>( N: number, alternative: Alternative, alpha: number, mu: number, sigmax: number, x: InputArray, strideX: number, offsetX: number, sigmay: number, y: InputArray, strideY: number, offsetY: number, out: T ): Results;
+	ndarray<T extends BaseResults>( NX: number, NY: number, alternative: Alternative, alpha: number, diff: number, sigmax: number, sigmay: number, x: InputArray, strideX: number, offsetX: number, y: InputArray, strideY: number, offsetY: number, out: T ): Results;
 }
 
 /**
 * Computes a two-sample Z-test for a strided array.
 *
-* @param N - number of indexed elements
+* @param NX - number of indexed elements in `x`
+* @param NY - number of indexed elements in `y`
 * @param alternative - alternative hypothesis
 * @param alpha - significance level
-* @param mu - mean under the null hypothesis
+* @param diff - difference in means under the null hypothesis
 * @param sigmax - known standard deviation of `x`
+* @param sigmay - known standard deviation of `y`
 * @param x - input array
 * @param strideX - stride length for `x`
-* @param sigmay - known standard deviation of `y`
 * @param y - input array
 * @param strideY - stride length for `y`
 * @param out - output results object
@@ -218,7 +221,7 @@ interface Routine {
 * var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
 *
 * var results = new Results();
-* var out = ztest2( x.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, results );
+* var out = ztest2( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, 2.0, x, 1, y, 1, results );
 * // returns {...}
 *
 * var bool = ( out === results );
@@ -231,7 +234,7 @@ interface Routine {
 * var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
 *
 * var results = new Results();
-* var out = ztest2.ndarray( x.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 0, 2.0, y, 1, 0, results );
+* var out = ztest2.ndarray( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, 2.0, x, 1, 0, y, 1, 0, results );
 * // returns {...}
 *
 * var bool = ( out === results );