[R] chisq.test() as a goodness of fit test

Achim Zeileis Achim.Zeileis at wu-wien.ac.at
Thu Jan 13 19:39:08 CET 2005


On Thu, 13 Jan 2005 18:23:37 +0100 (CET) Vito Ricci wrote:

> Dear R-Users,
> 
> How can I use chisq.test() as a goodness of fit test?
> Reading man-page I’ve some doubts that kind of test is
> available with this statement. Am I wrong?
> 
> X2=sum((O-E)^2)/E)
> 
> O=empirical frequencies
> E=expected freq.

You can do
  chisq.test(O, p = E/sum(E))
but note that this assumes that the expected frequencies/probabilities
are known (and not estimated).

> calculated with the model (such as normal distribution)

"Normal distribution" is not a fully specified model! If you estimate
the parameters by ML, the inference will typically not be valid. Another
approach would be to estimate the parameters by grouped ML or minimum
Chi-squared instead. See also ?pearson.test from package nortest and the
references therein.
For discrete distributions, this Chi-squared statistic is more natural
(though not always without problems): see ?goodfit in package vcd.
Z


> See:
> http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm
> for X2 used as a goodness of fit test.
> 
> Any help will be appreciated.
> Thank a lot. Bye.
> Vito
> 
> 
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