@stdlib/stats/base/dists/negative-binomial/ctor/README.md

Standard library statistical functions.

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# Negative Binomial

> Negative binomial distribution constructor.

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## Usage

```javascript
var NegativeBinomial = require( '@stdlib/stats/base/dists/negative-binomial/ctor' );
```

#### NegativeBinomial( \[r, p] )

Returns a [negative binomial][negative-binomial-distribution] distribution object.

```javascript
var nbinomial = new NegativeBinomial();

var mu = nbinomial.mean;
// returns 1.0
```

By default, `r = 1.0` and `p = 0.5`. To create a distribution having a different `r` (number of trials until experiment is stopped) and `p` (success probability), provide the corresponding arguments.

```javascript
var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var mu = nbinomial.mean;
// returns 16.0
```

* * *

## nbinomial

A [negative binomial][negative-binomial-distribution] distribution object has the following properties and methods...

### Writable Properties

#### nbinomial.r

Number of trials of the distribution. `r` **must** be a positive number.

```javascript
var nbinomial = new NegativeBinomial();

var r = nbinomial.r;
// returns 1.0

nbinomial.r = 4.5;

r = nbinomial.r;
// returns 4.5
```

#### nbinomial.p

Success probability of the distribution. `p` **must** be a number between 0 and 1.

```javascript
var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var p = nbinomial.p;
// returns 0.2

nbinomial.p = 0.7;

p = nbinomial.p;
// returns 0.7
```

* * *

### Computed Properties

#### NegativeBinomial.prototype.kurtosis

Returns the [excess kurtosis][kurtosis].

```javascript
var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var kurtosis = nbinomial.kurtosis;
// returns ~0.522
```

#### NegativeBinomial.prototype.mean

Returns the [expected value][expected-value].

```javascript
var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var mu = nbinomial.mean;
// returns ~18.0
```

#### NegativeBinomial.prototype.mode

Returns the [mode][mode].

```javascript
var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var mode = nbinomial.mode;
// returns 16.0
```

#### NegativeBinomial.prototype.skewness

Returns the [skewness][skewness].

```javascript
var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var skewness = nbinomial.skewness;
// returns ~0.596
```

#### NegativeBinomial.prototype.stdev

Returns the [standard deviation][standard-deviation].

```javascript
var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var s = nbinomial.stdev;
// returns ~6.708
```

#### NegativeBinomial.prototype.variance

Returns the [variance][variance].

```javascript
var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var s2 = nbinomial.variance;
// returns ~45.0
```

* * *

### Methods

#### NegativeBinomial.prototype.cdf( x )

Evaluates the [cumulative distribution function][cdf] (CDF).

```javascript
var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.cdf( 3.5 );
// returns ~0.033
```

#### NegativeBinomial.prototype.logpmf( x )

Evaluates the natural logarithm of the [probability mass function][pmf] (PMF).

```javascript
var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.logpmf( 4.0 );
// returns ~-3.775
```

#### NegativeBinomial.prototype.mgf( t )

Evaluates the [moment-generating function][mgf] (MGF).

```javascript
var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.mgf( 0.1 );
// returns ~1.66
```

#### NegativeBinomial.prototype.pmf( x )

Evaluates the [probability mass function][pmf] (PMF).

```javascript
var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.pmf( 4.0 );
// returns ~0.023
```

#### NegativeBinomial.prototype.quantile( p )

Evaluates the [quantile function][quantile-function] at probability `p`.

```javascript
var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.quantile( 0.5 );
// returns 15.0

y = nbinomial.quantile( 1.9 );
// returns NaN
```

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* * *

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## Examples

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```javascript
var NegativeBinomial = require( '@stdlib/stats/base/dists/negative-binomial/ctor' );

var nbinomial = new NegativeBinomial( 10.0, 0.4 );

var mu = nbinomial.mean;
// returns 15.0

var mode = nbinomial.mode;
// returns 13.0

var s2 = nbinomial.variance;
// returns ~37.5

var y = nbinomial.cdf( 8.0 );
// returns ~0.135
```

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[negative-binomial-distribution]: https://en.wikipedia.org/wiki/Negative_binomial_distribution

[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function

[mgf]: https://en.wikipedia.org/wiki/Moment-generating_function

[pmf]: https://en.wikipedia.org/wiki/Probability_mass_function

[quantile-function]: https://en.wikipedia.org/wiki/Quantile_function

[expected-value]: https://en.wikipedia.org/wiki/Expected_value

[kurtosis]: https://en.wikipedia.org/wiki/Kurtosis

[mode]: https://en.wikipedia.org/wiki/Mode_%28statistics%29

[skewness]: https://en.wikipedia.org/wiki/Skewness

[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation

[variance]: https://en.wikipedia.org/wiki/Variance

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