# GEV: GEV In ROOPSD: R Object Oriented Programming for Statistical Distribution

 GEV R Documentation

## GEV

### Description

GEV distribution in OOP way. Based on AbstractDist

### Details

See AbstractDist for generic methods

### Super class

`ROOPSD::AbstractDist` -> `GEV`

### Active bindings

`loc`

[double] location of the GEV law

`scale`

[double] scale of the GEV law

`shape`

[double] shape of the GEV law

`params`

[vector] params of the GEV law

### Methods

#### Public methods

Inherited methods

#### Method `new()`

Create a new GEV object.

##### Usage
`GEV\$new(loc = 0, scale = 1, shape = -0.1)`
##### Arguments
`loc`

[double] location parameter

`scale`

[double] scale parameter

`shape`

[double] shape parameter

##### Returns

A new 'GEV' object.

#### Method `qgradient()`

##### Usage
`GEV\$qgradient(p, lower.tail = TRUE)`
##### Arguments
`p`

[vector] Probabilities

`lower.tail`

[bool] If CDF or SF.

#### Method `pgradient()`

##### Usage
`GEV\$pgradient(x, lower.tail = TRUE)`
##### Arguments
`x`

[vector] Quantiles

`lower.tail`

[bool] If CDF or SF.

#### Method `clone()`

The objects of this class are cloneable with this method.

##### Usage
`GEV\$clone(deep = FALSE)`
##### Arguments
`deep`

Whether to make a deep clone.

### Examples

``````## Generate sample
loc   = 0
scale = 0.5
shape = -0.3
gev = ROOPSD::GEV\$new( loc = loc , scale = scale , shape = shape )
X   = gev\$rvs( n = 1000 )

## And fit parameters
gev\$fit(X)

``````

ROOPSD documentation built on Sept. 11, 2023, 9:06 a.m.