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feat: add docs
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‎lib/node_modules/@stdlib/stats/strided/dztest2/docs/repl.txt‎

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{{alias}}( NX, NY, alt, alpha, d, sdx, x, sx, sdy, y, sy, out )
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Computes a two-sample Z-test for double-precision floating-point strided
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arrays.
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The `N` and stride parameters determine which elements in the strided
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arrays are accessed at runtime.
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Indexing is relative to the first index. To introduce an offset, use a typed
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array view.
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Parameters
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----------
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NX: integer
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Number of indexed elements in `x`.
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NY: integer
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Number of indexed elements in `y`.
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alternative: string
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Alternative hypothesis. Must be one of the following:
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- two-sided: `x` has the same mean as `y`.
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- greater: `x` has a larger mean than `y`.
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- less: `x` has a smaller mean than `y`.
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alpha: number
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Significance level.
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d: number
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Difference in means under the null hypothesis.
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sdx: number
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Known standard deviation of `x`.
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x: Float64Array
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First input array.
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strideX: integer
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Stride length for `x`.
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sdy: number
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Known standard deviation of `y`.
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y: Float64Array
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Second input array.
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strideY: integer
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Stride length for `y`.
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out: Object
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Output results object.
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Returns
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-------
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out: Object
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Results object.
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Examples
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--------
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> var x = new {{alias:@stdlib/array/float64}}( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
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> var y = new {{alias:@stdlib/array/float64}}( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
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> var NX = x.length;
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> var NY = y.length;
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> var alt = 'two-sided';
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> var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}();
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> var res = {{alias}}( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, out );
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> res.toString()
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{{alias}}.ndarray( NX, NY, alt, alpha, d, sdx, x, sx, ox, sdy, y, sy, oy, out )
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Computes a two-sample Z-test for double-precision floating-point strided
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arrays using alternative indexing semantics.
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While typed array views mandate a view offset based on the underlying
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buffer, offset parameters support indexing semantics based on starting
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indices.
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Parameters
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----------
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NX: integer
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Number of indexed elements in `x`.
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NY: integer
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Number of indexed elements in `y`.
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alternative: string
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Alternative hypothesis. Must be one of the following:
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- two-sided: `x` has the same mean as `y`.
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- greater: `x` has a larger mean than `y`.
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- less: `x` has a smaller mean than `y`.
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alpha: number
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Significance level.
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d: number
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Difference in means under the null hypothesis.
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sdx: number
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Known standard deviation of `x`.
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x: Float64Array
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First input array.
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strideX: integer
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Stride length for `x`.
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offsetX: integer
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Starting index for `x`.
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sdy: number
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Known standard deviation of `y`.
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y: Float64Array
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Second input array.
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strideY: integer
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Stride length for `y`.
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offsetY: integer
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Starting index for `y`.
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out: Object
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Output results object.
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Returns
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-------
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out: Object
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Results object.
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Examples
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--------
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> var x = new {{alias:@stdlib/array/float64}}( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
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> var y = new {{alias:@stdlib/array/float64}}( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
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> var NX = x.length;
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> var NY = y.length;
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> var alt = 'two-sided';
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> var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}();
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> var res = {{alias}}.ndarray( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 0, 2.0, x, 1, 0, out );
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> res.toString()
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See Also
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--------
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‎lib/node_modules/@stdlib/stats/strided/dztest2/docs/types/index.d.ts‎

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/*
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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// TypeScript Version: 4.1
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/**
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* Alternative hypothesis.
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*/
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type Alternative = 'two-sided' | 'greater' | 'less';
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/**
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* Interface describing options when serializing a results object to a string.
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*/
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interface Options {
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/**
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* Number of digits to display after decimal points. Default: 4.
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*/
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digits?: number;
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/**
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* Boolean indicating whether to show the test decision. Default: true.
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*/
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decision?: boolean;
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}
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/**
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* Serializes a results object as a string.
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*
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* @returns string representation
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*/
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type toString = ( options?: Options ) => string;
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/**
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* Serializes a results object as a JSON object.
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*
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* @returns JSON representation
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*/
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type toJSON = () => BaseResults;
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/**
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* Interface describing a "base" results object.
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*/
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interface BaseResults {
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/**
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* Boolean indicating whether the null hypothesis was rejected.
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*/
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rejected: boolean;
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/**
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* Alternative hypothesis.
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*/
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alternative: Alternative;
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/**
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* Significance level.
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*/
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alpha: number;
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/**
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* p-value.
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*/
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pValue: number;
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/**
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* Test statistic.
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*/
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statistic: number;
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/**
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* Confidence interval.
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*/
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ci: Float64Array;
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/**
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* Value of the mean under the null hypothesis
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*/
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nullValue: number;
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/**
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* Sample mean of `x`.
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*/
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xmean: number;
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/**
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* Sample mean of `y`.
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*/
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ymean: number;
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}
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/**
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* Interface describing a results object.
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*/
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interface Results extends BaseResults {
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/**
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* Serializes results as formatted test output.
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*/
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toString: toString;
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/**
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* Serializes results as JSON.
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*/
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toJSON: toJSON;
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}
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/**
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* Interface describing `dztest2`.
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*/
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interface Routine {
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/**
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* Computes a two-sample Z-test for double-precision floating-point strided arrays.
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*
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* @param NX - number of indexed elements in `x`
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* @param NY - number of indexed elements in `y`
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* @param alternative - alternative hypothesis
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* @param alpha - significance level
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* @param diff - difference in means under the null hypothesis
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* @param sigmax - known standard deviation of `x`
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* @param x - first input array
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* @param strideX - stride length for `x`
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* @param sigmay - known standard deviation of `y`
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* @param y - second input array
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* @param strideY - stride length for `y`
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* @param out - output results object
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* @returns results object
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
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*
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* var x = new Float64Array( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
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* var y = new Float64Array( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
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*
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* var results = new Results();
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* var out = dztest2( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, results );
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* // returns {...}
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*
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* var bool = ( out === results );
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* // returns true
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*/
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<T extends BaseResults>( NX: number, NY: number, alternative: Alternative, alpha: number, diff: number, sigmax: number, x: Float64Array, strideX: number, sigmay: number, y: Float64Array, strideY: number, out: T ): Results;
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/**
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* Computes a two-sample Z-test for double-precision floating-point strided arrays using alternative indexing semantics.
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*
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* @param NX - number of indexed elements in `x`
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* @param NY - number of indexed elements in `y`
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* @param alternative - alternative hypothesis
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* @param alpha - significance level
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* @param diff - difference in means under the null hypothesis
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* @param sigmax - known standard deviation of `x`
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* @param x - first input array
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* @param strideX - stride length for `x`
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* @param offsetX - starting index for `x`
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* @param sigmay - known standard deviation of `y`
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* @param y - second input array
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* @param strideY - stride length for `y`
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* @param offsetY - starting index for `y`
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* @param out - output results object
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* @returns results object
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
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*
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* var x = new Float64Array( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
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* var y = new Float64Array( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
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*
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* var results = new Results();
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* var out = dztest2.ndarray( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 0, 2.0, y, 1, 0, results );
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* // returns {...}
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*
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* var bool = ( out === results );
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* // returns true
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*/
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ndarray<T extends BaseResults>( NX: number, NY: number, alternative: Alternative, alpha: number, diff: number, sigmax: number, x: Float64Array, strideX: number, offsetX: number, sigmay: number, y: Float64Array, strideY: number, offsetY: number, out: T ): Results;
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}
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/**
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* Computes a two-sample Z-test for double-precision floating-point strided arrays.
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*
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* @param NX - number of indexed elements in `x`
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* @param NY - number of indexed elements in `y`
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* @param alternative - alternative hypothesis
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* @param alpha - significance level
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* @param diff - difference in means under the null hypothesis
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* @param sigmax - known standard deviation of `x`
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* @param x - first input array
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* @param strideX - stride length for `x`
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* @param sigmay - known standard deviation of `y`
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* @param y - second input array
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* @param strideY - stride length for `y`
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* @param out - output results object
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* @returns results object
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
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*
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* var x = new Float64Array( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
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* var y = new Float64Array( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
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*
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* var results = new Results();
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* var out = dztest2( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, results );
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* // returns {...}
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*
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* var bool = ( out === results );
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* // returns true
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
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*
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* var x = new Float64Array( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
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* var y = new Float64Array( [ 3.0, 3.0, 5.0, 7.0, 7.0 ] );
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*
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* var results = new Results();
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* var out = dztest2.ndarray( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 0, 2.0, y, 1, 0, results );
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* // returns {...}
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*
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* var bool = ( out === results );
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* // returns true
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*/
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declare var dztest2: Routine;
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// EXPORTS //
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export = dztest2;

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