[R] Statistical question re assessing fit of distribution functions.

[Ted Byers]

I am in a situation where I have to fit a distrution, such as cauchy or
normal, to an empirical dataset.  Well and good, that is easy.

But I wanted to assess just how good the fit is, using ks.test.

I am concerned about the following note in the docs (about the example
provided):  "Note that the distribution theory is not valid here as we have
estimated the parameters of the normal distribution from the same sample"

This implies I should not use ks.test(x,"pnorm",mean =1.187, sd =0.917),
where the numbers shown are estimated from 'x'.  If this is so, how do I get
a correct test?  I know I can not use different samples because of just how
different the parameters are from one sample to the next, so using
parameters estimated from the sample from week one to define the
distribution function for ks.test will give a poor fit for the data from
week two.  And the sample size is small enough that I would not have
confidence in the parameters estimated from a portion of a samlpe to fit
against the remainder of the sample.

Thanks

Ted

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