npm package: @stdlib/stats-wilcoxon
Description: Wilcoxon signed rank test.
Author: The Stdlib Authors
Latest version: 0.2.3

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# Wilcoxon Signed Rank Test

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> One-sample and paired Wilcoxon signed rank test.

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-wilcoxon
```

</section>

<section class="usage">

## Usage

```javascript
var wilcoxon = require( '@stdlib/stats-wilcoxon' );
```

#### wilcoxon( x\[, y]\[, opts] )

Performs a one-sample t-test for the null hypothesis that the data in [array][mdn-array] or [typed array][mdn-typed-array] `x` is drawn from a distribution that is symmetric around zero (i.e., with median zero).

```javascript
// Differences in plant heights, see Cureton (1967)
var x = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];
var out = wilcoxon( x );
/* e.g., returns
    {
        'rejected': true,
        'alpha': 0.05,
        'pValue': 0.04125976562499978,
        'statistic': 96,
        // ...
    }
*/
```

When [array][mdn-array] or [typed array][mdn-typed-array] `y` is supplied, the function tests whether the paired differences `x - y` come from a distribution that is symmetric around zero (i.e., with median zero).

```javascript
// Patient measurements at first (x) and second (y) visit, see Hollander & Wolfe (1973)
var x = [ 1.83, 0.50, 1.62, 2.48, 1.68, 1.88, 1.55, 3.06, 1.30 ];
var y = [ 0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29 ];

var out = wilcoxon( x, y );
/* e.g., returns
    {
        'rejected': true,
        'alpha': 0.05,
        'pValue': 0.0390625,
        'statistic': 40,
        // ...
    }
*/
```

The returned object comes with a `.print()` method which when invoked will print a formatted output of the hypothesis test results. `print` accepts a `digits` option that controls the number of decimal digits displayed for the outputs and a `decision` option, which when set to `false` will hide the test decision.

<!-- run-disable -->

```javascript
console.log( out.print() );
/* e.g., =>
    Paired Wilcoxon signed rank test

    Alternative hypothesis: Median of the difference `x - y` is not equal to 0

        pValue: 0.0391
        statistic: 40

    Test Decision: Reject null in favor of alternative at 5% significance level
*/
```

The `wilcoxon` function accepts the following `options`:

-   **alpha**: `number` in the interval `[0,1]` giving the significance level of the hypothesis test. Default: `0.05`.
-   **alternative**: Either `two-sided`, `less` or `greater`. Indicates whether the alternative hypothesis is that the mean of `x` is larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to `mu` (`two-sided`). Default: `two-sided`.
-   **correction**: continuity correction adjusting the Wilcoxon rank statistic by 0.5 towards the mean when using the normal approximation. Default: `true`.
-   **exact**: Determines whether to force use of the exact distribution instead of a normal approximation when there are more than fifty data points. Default: `false`.
-   **mu**: `number` denoting the hypothesized median under the null hypothesis. Default: `0`.
-   **zeroMethod**:  Method governing how zero-differences are handled (`pratt`, `wilcox`, or `zsplit`). Default: `'wilcox'`.

By default, the hypothesis test is carried out at a significance level of `0.05`. To choose a different significance level, set the `alpha` option.

```javascript
var table;
var out;
var arr;

arr = [ 2, 4, 3, 1, 0 ];
out = wilcoxon( arr, {
    'alpha': 0.01
});
table = out.print();
/* e.g., returns
    One-Sample Wilcoxon signed rank test

    Alternative hypothesis: Median of `x` is not equal to 0

        pValue: 0.035
        statistic: 21

    Test Decision: Reject null in favor of alternative at 5% significance level
*/

out = wilcoxon( arr, {
    'alpha': 0.1
});
table = out.print();
/* e.g., returns
    One-Sample Wilcoxon signed rank test

    Alternative hypothesis: Median of `x` is not equal to 0

        pValue: 0.035
        statistic: 21

    Test Decision: Fail to reject null in favor of alternative at 1% significance level
*/
```

To test whether the data comes from a distribution with a median different than zero, set the `mu` option.

```javascript
var arr = [ 4, 4, 6, 6, 5 ];
var out = wilcoxon( arr, {
    'mu': 5
});
/* e.g., returns
{
    'rejected': false,
    'pValue': 1,
    'statistic': 0,
    // ...
}
*/
```

By default, a two-sided test is performed. To perform either of the one-sided tests, set the `alternative` option to `less` or `greater`.

```javascript
var arr = [ 4, 4, 6, 6, 5 ];
var out = wilcoxon( arr, {
    'alternative': 'less'
});
var table = out.print();
/* e.g., returns
    One-Sample Wilcoxon signed rank test

    Alternative hypothesis: Median of `x` is less than 0

        pValue: 0.9853
        statistic: 15

    Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/

out = wilcoxon( arr, {
    'alternative': 'greater'
});
table = out.print();
/* e.g., returns
    One-Sample Wilcoxon signed rank test

    Alternative hypothesis: Median of `x` is greater than 0

        pValue: 0.0284
        statistic: 15

    Test Decision: Reject null in favor of alternative at 5% significance level
*/
```

By default, all zero-differences are discarded before calculating the ranks. Set `zeroMethod` to `pratt` when you wish differences of zero to be used in the rank calculation but then drop them or to `zsplit` when differences of zero are shall be used in the ranking procedure and the ranks then split between positive and negative ones.

```javascript
var arr = [ 0, 2, 3, -1, -4, 0, 0, 8, 9 ];
var out = wilcoxon( arr, {
    'zeroMethod': 'pratt'
});
/* e.g., returns
    {
        'rejected': false,
        'alpha': 0.05,
        'pValue': ~0.331,
        'statistic': 28,
        // ...
    }
*/

out = wilcoxon( arr, {
    'zeroMethod': 'zsplit'
});
/* e.g., returns
    {
        'rejected': false,
        'alpha': 0.05,
        'pValue': ~0.342,
        'statistic': 31,
        // ...
    }
*/
```

By default, the test uses the exact distribution of the rank statistic to calculate the critical values for the test in case of no ties and no zero-differences. Since it is more computationally efficient, starting with fifty observations a normal approximation is employed. If you would like the test to use the correct distribution even for larger samples, set the `exact` option to `true`.

```javascript
var normal = require( '@stdlib/random-array-normal' );

var rnorm = normal.factory( 0.0, 4.0, {
    'seed': 100
});
var arr = rnorm( 100 );

var out = wilcoxon( arr, {
    'exact': false
});
/* e.g., returns
    {
        'rejected': false,
        'alpha': 0.05,
        'pValue': ~0.422,
        'statistic': 2291,
        // ...
    }
*/

out = wilcoxon( arr, {
    'exact': true
});
/* e.g., returns
    {
        'rejected': false,
        'alpha': 0.05,
        'pValue': ~0.424,
        'statistic': 2291,
        // ...
    }
*/
```

By default, when using the normal approximation, the test uses a continuity correction, which adjusts the Wilcoxon rank statistic by `0.5` towards the mean. To disable this correction, set `correction` to `false`.

```javascript
var normal = require( '@stdlib/random-array-normal' );

var rnorm = normal.factory( 0.0, 4.0, {
    'seed': 100
});
var arr = rnorm( 100 );

var out = wilcoxon( arr, {
    'correction': false
});
/* e.g., returns
    {
        'rejected': false,
        'alpha': 0.05,
        'pValue': ~0.421,
        'statistic': 2291,
        // ...
    }
*/

out = wilcoxon( arr, {
    'correction': true
});
/* e.g., returns
    {
        'rejected': false,
        'alpha': 0.05,
        'pValue': ~0.422,
        'statistic': 2291,
        // ...
    }
*/
```

</section>

<!-- /.usage -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var uniform = require( '@stdlib/random-array-discrete-uniform' );
var wilcoxon = require( '@stdlib/stats-wilcoxon' );

var runif = uniform.factory( -50.0, 50.0, {
    'seed': 37827
});
var arr = runif( 100 );

// Test whether distribution is symmetric around zero:
var out = wilcoxon( arr );
var table = out.print();
/* e.g., returns
    One-Sample Wilcoxon signed rank test

    Alternative hypothesis: Median of `x` is not equal to 0

        pValue: 0.7714
        statistic: 2438.5

    Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/

// Test whether distribution has median of five:
out = wilcoxon( arr, {
    'mu': 5.0
});
table = out.print();
/* e.g, returns
    One-Sample Wilcoxon signed rank test

    Alternative hypothesis: Median of `x` is not equal to 5

        pValue: 0.0529
        statistic: 1961.5

    Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/
```

</section>

<!-- /.examples -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

* * *

## See Also

-   <span class="package-name">[`@stdlib/stats-ttest`][@stdlib/stats/ttest]</span><span class="delimiter">: </span><span class="description">one-sample and paired Student's t-Test.</span>
-   <span class="package-name">[`@stdlib/stats-ztest`][@stdlib/stats/ztest]</span><span class="delimiter">: </span><span class="description">one-sample and paired z-Test.</span>

</section>

<!-- /.related -->

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<section class="main-repo" >

* * *

## Notice

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For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib].

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---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

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