Usage

`javascript
var Poisson = require( '@stdlib/stats-base-dists-poisson-ctor' );
`

#### Poisson( \[lambda] )

Returns an [Poisson][poisson-distribution] distribution object.

`javascript
var poisson = new Poisson();

var lambda = poisson.mean;
// returns 1.0
`

By default, lambda = 1.0. To create a distribution having a different mean parameter lambda, provide a parameter value.

`javascript
var poisson = new Poisson( 4.0 );

var lambda = poisson.mean;
// returns 4.0
`

*

poisson

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

$3

#### poisson.lambda

Mean parameter of the distribution. lambda must be a positive number.

`javascript
var poisson = new Poisson( 2.0 );

var lambda = poisson.lambda;
// returns 2.0

poisson.lambda = 3.0;

lambda = poisson.lambda;
// returns 3.0
`

*

$3

#### Poisson.prototype.entropy

Returns the [differential entropy][entropy].

`javascript
var poisson = new Poisson( 4.0 );

var entropy = poisson.entropy;
// returns ~2.087
`

#### Poisson.prototype.kurtosis

Returns the [excess kurtosis][kurtosis].

`javascript
var poisson = new Poisson( 4.0 );

var kurtosis = poisson.kurtosis;
// returns 0.25
`

#### Poisson.prototype.mean

Returns the [median][expected-value].

`javascript
var poisson = new Poisson( 4.0 );

var mu = poisson.mean;
// returns 4.0
`

#### Poisson.prototype.median

Returns the [median][median].

`javascript
var poisson = new Poisson( 4.0 );

var median = poisson.median;
// returns 4.0
`

#### Poisson.prototype.mode

Returns the [mode][mode].

`javascript
var poisson = new Poisson( 4.0 );

var mode = poisson.mode;
// returns 4.0
`

#### Poisson.prototype.skewness

Returns the [skewness][skewness].

`javascript
var poisson = new Poisson( 4.0 );

var skewness = poisson.skewness;
// returns 0.5
`

#### Poisson.prototype.stdev

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

`javascript
var poisson = new Poisson( 4.0 );

var s = poisson.stdev;
// returns 2.0
`

#### Poisson.prototype.variance

Returns the [variance][variance].

`javascript
var poisson = new Poisson( 4.0 );

var s2 = poisson.variance;
// returns 4.0
`

*

$3

#### Poisson.prototype.cdf( x )

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

`javascript
var poisson = new Poisson( 2.0 );

var y = poisson.cdf( 0.5 );
// returns ~0.135
`

#### Poisson.prototype.logpmf( x )

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

`javascript
var poisson = new Poisson( 2.0 );

var y = poisson.logpmf( 3.0 );
// returns ~-1.712

y = poisson.logpmf( 2.3 );
// returns -Infinity
`

#### Poisson.prototype.mgf( t )

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

`javascript
var poisson = new Poisson( 2.0 );

var y = poisson.mgf( 0.5 );
// returns ~3.66
`

#### Poisson.prototype.pmf( x )

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

`javascript
var poisson = new Poisson( 2.0 );

var y = poisson.pmf( 3.0 );
// returns ~0.18

y = poisson.pmf( 2.3 );
// returns 0.0
`

#### Poisson.prototype.quantile( p )

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

`javascript
var poisson = new Poisson( 2.0 );

var y = poisson.quantile( 0.5 );
// returns 2.0

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