Re: [R] Goodness of fit test for estimated distribution
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/
###
ich empfehle www.boag-online.de
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Re: [R] Goodness of fit test for estimated distribution
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/
###
ich empfehle www.boag-online.de
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
__
[EMAIL PROTECTED] mailing list
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[R] Goodness of fit test for estimated distribution
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/ ### ich empfehle www.boag-online.de __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
