MLE_LambertW.default {LambertW}R Documentation

Maximum Likelihood Estimation

Description

MLE of Lambert W RV for Gaussian and student-t input.

Usage

## Default S3 method:
MLE_LambertW(y, distname = c("normal"), theta.0 = IGMM(y)$theta)

Arguments

y data
distname input distribution. By defaul "normal". Alternative "t"
theta.0 Starting value for numerical optimization. By default the GMM estimate.

Value

An object of class LWest

data the data
theta.0 initial value
theta MLE for theta
logLH log-likelihood function (argument for the summary function to calculate the Hessian numerically)
call function call
message message from the optimization method. What kind of convergence?
distname input distribution
method Estimation method. Here "MLE"

Author(s)

Georg M. Goerg

References

Goerg, G.M. (2009). “Lambert W Random Variables - A new class of skewed distribution functions”. Unpublished

Examples

data(AA)
attach(AA)

X=AA[AA$sex=="f",]
y=X$bmi

fit.ml=MLE_LambertW(y)
summary(fit.ml)
plot(fit.ml)

[Package LambertW version 0.1.6 Index]