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

Standard library statistical functions.

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# Binomial

> Binomial distribution constructor.

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## Usage

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

#### Binomial( \[n, p] )

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

```javascript
var binomial = new Binomial();

var mu = binomial.mean;
// returns 0.5
```

By default, `n = 1` and `p = 0.5`, which corresponds to a [Bernoulli][bernoulli-distribution] distribution. To create a distribution having a different `n` (number of trials) and `p` (success probability), provide the corresponding arguments.

```javascript
var binomial = new Binomial( 4, 0.2 );

var mu = binomial.mean;
// returns 0.8
```

* * *

## binomial

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

### Writable Properties

#### binomial.n

Number of trials of the distribution. `n` **must** be a positive integer.

```javascript
var binomial = new Binomial();

var n = binomial.n;
// returns 1.0

binomial.n = 4;

n = binomial.n;
// returns 4.0
```

#### binomial.p

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

```javascript
var binomial = new Binomial( 4, 0.2 );

var p = binomial.p;
// returns 0.2

binomial.p = 0.7;

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

* * *

### Computed Properties

#### Binomial.prototype.kurtosis

Returns the [excess kurtosis][kurtosis].

```javascript
var binomial = new Binomial( 12, 0.4 );

var kurtosis = binomial.kurtosis;
// returns ~-0.153
```

#### Binomial.prototype.mean

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

```javascript
var binomial = new Binomial( 12, 0.4 );

var mu = binomial.mean;
// returns ~4.8
```

#### Binomial.prototype.median

Returns the [median][median].

```javascript
var binomial = new Binomial( 12, 0.4 );

var median = binomial.median;
// returns 5.0
```

#### Binomial.prototype.mode

Returns the [mode][mode].

```javascript
var binomial = new Binomial( 12, 0.4 );

var mode = binomial.mode;
// returns 5.0
```

#### Binomial.prototype.skewness

Returns the [skewness][skewness].

```javascript
var binomial = new Binomial( 12, 0.4 );

var skewness = binomial.skewness;
// returns ~0.118
```

#### Binomial.prototype.stdev

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

```javascript
var binomial = new Binomial( 12, 0.4 );

var s = binomial.stdev;
// returns ~1.697
```

#### Binomial.prototype.variance

Returns the [variance][variance].

```javascript
var binomial = new Binomial( 12, 0.4 );

var s2 = binomial.variance;
// returns ~2.88
```

* * *

### Methods

#### Binomial.prototype.cdf( x )

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

```javascript
var binomial = new Binomial( 4, 0.2 );

var y = binomial.cdf( 0.5 );
// returns ~0.41
```

#### Binomial.prototype.logpmf( x )

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

```javascript
var binomial = new Binomial( 4, 0.2 );

var y = binomial.logpmf( 2.0 );
// returns ~-1.873
```

#### Binomial.prototype.mgf( t )

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

```javascript
var binomial = new Binomial( 4, 0.2 );

var y = binomial.mgf( 0.5 );
// returns ~1.629
```

#### Binomial.prototype.pmf( x )

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

```javascript
var binomial = new Binomial( 4, 0.2 );

var y = binomial.pmf( 2.0 );
// returns ~0.154
```

#### Binomial.prototype.quantile( p )

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

```javascript
var binomial = new Binomial( 4, 0.2 );

var y = binomial.quantile( 0.5 );
// returns 1.0

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

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* * *

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## Examples

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

var binomial = new Binomial( 10, 0.4 );

var mu = binomial.mean;
// returns 4.0

var mode = binomial.mode;
// returns 4.0

var s2 = binomial.variance;
// returns 2.4

var y = binomial.cdf( 0.8 );
// returns ~0.006
```

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[bernoulli-distribution]: https://en.wikipedia.org/wiki/Bernoulli_distribution

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

[median]: https://en.wikipedia.org/wiki/Median

[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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