Methods for Lambert W input and output objects

Description

S3 methods for Lambert W input and output objects (created by create_LambertW_input and create_LambertW_output).

plot.LambertW_input plots the theoretical (1) pdf and (2) cdf of the input X sim F_X(x mid oldsymbol β).

plot.LambertW_output plots the theoretical (1) pdf and (2) cdf of the output RV Y sim Lambert W \times F_X(x mid oldsymbol β). It overlays the plot with the pdf and cdf of the input RV X sim F_X(x mid oldsymbol β) (setting γ = δ = 0, α = 1).

print.LambertW_input prints an overview of the input object.

print.LambertW_output prints an overview of the output object.

Usage

## S3 method for class 'LambertW_input'
plot(x, xlim = NULL, ...)

## S3 method for class 'LambertW_output'
plot(x, xlim = NULL, ...)

## S3 method for class 'LambertW_input'
print(x, ...)

## S3 method for class 'LambertW_output'
print(x, ...)

Arguments

Examples

# create a Normal(1, 2) input
Gauss.input <- create_LambertW_input("normal", beta = c(1, 2))
plot(Gauss.input)
# make it a bit heavy tailed (beta in theta comes from Gauss.input)
LW.Gauss <- create_LambertW_output(LambertW.input = Gauss.input, 
                                   theta = list(delta = c(0.3)))
LW.Gauss  # print a nice overview in the console
plot(LW.Gauss)

# draw random sample
LW.Gauss$r(n=10)
Gauss.input$r(n=10)
# quantiles
LW.Gauss$q(p=0.6)
Gauss.input$q(p=0.6)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(LambertW)
Loading required package: MASS
Loading required package: ggplot2
This is 'LambertW' version 0.6.4.  Please see the NEWS file and citation("LambertW").

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/LambertW/LambertW_input_output-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: LambertW_input_output-methods
> ### Title: Methods for Lambert W input and output objects
> ### Aliases: LambertW_input_output-methods plot.LambertW_input
> ###   plot.LambertW_output print.LambertW_input print.LambertW_output
> ### Keywords: hplot print
> 
> ### ** Examples
> 
> 
> # create a Normal(1, 2) input
> Gauss.input <- create_LambertW_input("normal", beta = c(1, 2))
> plot(Gauss.input)
> # make it a bit heavy tailed (beta in theta comes from Gauss.input)
> LW.Gauss <- create_LambertW_output(LambertW.input = Gauss.input, 
+                                    theta = list(delta = c(0.3)))
> LW.Gauss  # print a nice overview in the console
 Input distribution: normal
 Output distribution: heavy-tail (one parameter) Lambert W x normal(1,2)
 with (input) parameters: mu=1, sigma=2
 and transformation parameters: delta = 0.3
> plot(LW.Gauss)
> 
> # draw random sample
> LW.Gauss$r(n=10)
 [1]  5.6522026 12.6399125  0.7813817 -0.6295115  1.6048207 -2.3463128
 [7] -0.4091832  1.6798287  0.7139503 -3.2406201
> Gauss.input$r(n=10)
 [1]  2.74392789 -2.24101242  0.06603732 -2.99629540  1.04636243  0.82995329
 [7] -0.83729877  0.21298392  1.27412672 -0.21095847
> # quantiles
> LW.Gauss$q(p=0.6)
[1] 1.511596
> Gauss.input$q(p=0.6)
[1] 1.506694
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>