npm package: @stdlib/stats-base-ndarray-dnanminabs
Description: Compute the minimum value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
Author: The Stdlib Authors
Latest version: 0.1.1

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<details>
  <summary>
    About stdlib...
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  <p>We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.</p>
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# dnanminabs

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

> Compute the minimum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.

<section class="intro">

</section>

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<section class="installation">

## Installation

```bash
npm install @stdlib/stats-base-ndarray-dnanminabs
```

</section>

<section class="usage">

## Usage

```javascript
var dnanminabs = require( '@stdlib/stats-base-ndarray-dnanminabs' );
```

#### dnanminabs( arrays )

Computes the minimum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.

```javascript
var Float64Array = require( '@stdlib/array-float64' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );

var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var v = dnanminabs( [ x ] );
// returns 1.0
```

The function has the following parameters:

-   **arrays**: array-like object containing a one-dimensional input ndarray.

</section>

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<section class="notes">

## Notes

-   If provided an empty one-dimensional ndarray, the function returns `NaN`.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var uniform = require( '@stdlib/random-base-uniform' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var bernoulli = require( '@stdlib/random-base-bernoulli' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var dnanminabs = require( '@stdlib/stats-base-ndarray-dnanminabs' );

function rand() {
    if ( bernoulli( 0.8 ) < 1 ) {
        return NaN;
    }
    return uniform( -50.0, 50.0 );
}

var xbuf = filledarrayBy( 10, 'float64', rand );
var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

var v = dnanminabs( [ x ] );
console.log( v );
```

</section>

<!-- /.examples -->

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<section class="related">

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<section class="main-repo" >

* * *

## Notice

This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

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].

#### Community

[![Chat][chat-image]][chat-url]

---

## License

See [LICENSE][stdlib-license].


## Copyright

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

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