Normal | R Documentation |
Normal distribution in OOP way. Based on AbstractDist
See AbstractDist for generic methods
ROOPSD::AbstractDist
-> Normal
mean
[double] mean of the normal law
sd
[double] standard deviation of the normal law
params
[vector] params of the normal law
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()
new()
Create a new Normal object.
Normal$new(mean = 0, sd = 1)
mean
[double] Mean of the normal law
sd
[double] Standard deviation of the normal law
A new 'Normal' object.
clone()
The objects of this class are cloneable with this method.
Normal$clone(deep = FALSE)
deep
Whether to make a deep clone.
## 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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.