LambertW-package {LambertW} | R Documentation |
Lambert W random variables (RV) offer a new way of dealing with slightly skewed data. It is based on an input/ouput framework - for details see References. This package contains the most important functions to perform an adequate analysis. Lambert W data can be simulated, parameters estimated and results can be plotted in a proper way. Quantile functions allow a more realistic analysis and inference of skewed data.
Package: | LambertW |
Type: | Package |
Version: | 0.1.5 |
Date: | 2009-03-21 |
License: | GPL-2 |
LazyLoad: | yes |
Georg M. Goerg <e0225792@student.tuwien.ac.at>
Maintainer: Georg M. Goerg <e0225792@student.tuwien.ac.at>
Goerg, G.M. (2009). “Lambert W Random Variables - A new class of skewed distribution functions”. Unpublished
data(AA) attach(AA) X=AA[AA$sex=="f",] y=X$bmi op=par(no.readonly=TRUE) par(mfrow=c(2,1), mar=c(2,4,3,1)) plot(y) hist(y, prob=TRUE, 15) lines(density(y)) par(op) fit.gmm=IGMM(y) summary(fit.gmm) # Delta is significant and positive plot(fit.gmm) # Comparison of Theoretical and Empirical Moments mom.LambertW.X.Gauss(fit.gmm$theta) rbind(mean(y), sd(y), skewness(y), kurtosis(y)) x=get.input(y, fit.gmm$theta)$x normfit(x) plot(fit.gmm) fit.ml=MLE_LambertW(y) summary(fit.ml) plot(fit.ml)