Normal {ROOPSD} | R Documentation |
Normal
Description
Normal distribution in OOP way. Based on AbstractDist
Details
See AbstractDist for generic methods
Super class
ROOPSD::AbstractDist
-> Normal
Active bindings
mean
[double] mean of the normal law
sd
[double] standard deviation of the normal law
params
[vector] params of the normal law
Methods
Public methods
Inherited methods
ROOPSD::AbstractDist$cdf()
ROOPSD::AbstractDist$density()
ROOPSD::AbstractDist$diagnostic()
ROOPSD::AbstractDist$fit()
ROOPSD::AbstractDist$icdf()
ROOPSD::AbstractDist$isf()
ROOPSD::AbstractDist$logdensity()
ROOPSD::AbstractDist$pdeltaCI()
ROOPSD::AbstractDist$qdeltaCI()
ROOPSD::AbstractDist$qgradient()
ROOPSD::AbstractDist$rvs()
ROOPSD::AbstractDist$sf()
Method new()
Create a new Normal object.
Usage
Normal$new(mean = 0, sd = 1)
Arguments
mean
[double] Mean of the normal law
sd
[double] Standard deviation of the normal law
Returns
A new 'Normal' object.
Method clone()
The objects of this class are cloneable with this method.
Usage
Normal$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
Examples
## Generate sample
mean = 1
sd = 0.5
norml = ROOPSD::Normal$new( mean = mean , sd = sd )
X = norml$rvs( n = 1000 )
## And fit parameters
norml$fit(X)
[Package ROOPSD version 0.3.9 Index]