[R] Help please..

[Jim Lindsey]

> 
> On Wed, 1 Mar 2000, Ajit K Jena wrote:
> > 
> > I am facing a peculiar problem and hope someone out there
> > can comment on it.
> > 
> > In goodness-of-fit tests for evaluation of distributions,
> > there are three well-known methods:
> > 
> > 	1. Chi-square
> > 	2. Anderson-Darling
> > 	3. Kolmogorov-Sminrov
> > 
> I would suggest you find the likelihood or some modified version of it
> (AIC). If the model describes data well, the likelihood is big. Of course
> you don't get a p-value, which in my book is a good thing. (Read the
> manifesto: AWF Edwards (1972/1992), Likelihood, Johns Hopkins U Press)

  I certainly would agree with that. That is essentially what all my
libraries do. For example, gnlr and gnlr3 in library gnlm when used
with a null model (no covariates) will allow the comparison of about
25 different distributions.

  You might also like to take a look at Chapter 4 of my Introductory
Statistics (OUP, 1995) which evaluates goodness of fit of a variety of
distributions when the data are in grouped frequency form, and the
accompanying R function, fit.dist in library gnlm (and for more
advance likelihood inference, my Parametric Statistical Inference,
OUP, 1996). Jim

> 
> Bill
> 
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