What about Monte Carlo? I recently produced (with help from
contributors to this list) qq plots for certain complicated mixtures of
distributions. To evaluate goodness of fit, I produced Monte Carlo
confidence intervals from 401 simulated qq plots and took the 11th and
391st of them for each quantile. {quantile(1:401, c(.025, .975)) =
c(11, 391)}. Something like this could be done to obtain a significance
level for ks.test, for example.
This may not be as satisfying for some purposes as a clean,
theoretical result, but it produced useful answers without busting the
project budget too badly.
hope this helps.
spencer graves
roger koenker wrote:
In full generality this is a quite difficult problem as discussed in
Durbin's (1973) SIAM monograph. An elegant general approach
is provided by Khmaladze
@article{Khma:Arie:1981,
author = {Khmaladze, E. V.},
title = {Martingale approach in the theory of goodness-of-fit tests},
year = {1981},
journal = {Theory of Probability and its Applications (Transl of
Teorija Verojatnostei i ee Primenenija)},
volume = {26},
pages = {240--257}
}
but I don't think that there is a general implementation of the
approach for R, or
any other software environment, for that matter.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
fax: 217-244-6678Champaign, IL 61820
On Jun 29, 2004, at 1:08 PM, Christian Hennig wrote:
Hi,
is there any method for goodness of fit testing of an (as general as
possible) univariate distribution with parameters estimated, for normal,
exponential, gamma distributions, say (e.g. the corrected p-values for
the Kolmogorov-Smirnov or Chi-squared with corresponding ML estimation
method)?
It seems that neither ks.test nor chisq.test handle estimated
parameters.
I am aware of function goodfit in package vcd, which seems to it for
some
discrete distributions.
Thank you for help,
Christian
***
Christian Hennig
Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg
[EMAIL PROTECTED], http://www.math.uni-hamburg.de/home/hennig/
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