Hello!
I am trying with this question again:
I would like to test few distributional assumptions for some behavioral
response data. There are few theories about true distribution of those
data, like: normal, lognormal, gamma, ex-Gaussian
(exponential-Gaussian), Wald (inverse Gaussian) etc. The best way would
be via qq-plot, to show to students differences. First two are trivial:
qqnorm(dat$X)
qqnorm(log(dat$X))
Then, things are getting more "hairy". I am not sure how to make plots
for the rest. I tried gamma with:
qqmath(~ X, data=dat, distribution=function(X)
qgamma(X, shape, scale))
Which should be the same as:
plot(qgamma(ppoints(dat$X), shape, scale), sort(dat$X))
Shape and scale parameters I got via mhsmm package that has gammafit()
for shape and scale parameters estimation.
Am I on right track? Does anyone know how to plot the rest: ex-Gaussian
(exponential-Gaussian), Wald (inverse Gaussian)?
Thanks,
PM
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