Goodness of fit measures for a distribution

Hi everyone,
I have a basic question regarding what are some common quantitative measures
for the goodness of (parametric) fit of a distribution.

Here is what I am trying to do. I have some sample data which lets say it
has a lognormal distribution. I can get some hints of how it is distributed
from the histogram. What I want to do, is fit a few distributions (e.g.
Lognromal, Beta, Gamma, inverse Gaussian etc) and find out which fits the
best.

I have carried out some fits uing maximum likelihood and I can plot the
pdfs, or cdfs over my data to see which fits the best. However, I need some
quantitative results (i.e. numbers). Just to point out that I am not really
interested at the parameters of the distributions, but only which fits the
best.

I could do Kolmogorov-Smirnov and chi-square tests but that's as far as I
know.

Would someone be able to tell me what sort of metrics I can use for my
problem?

Regards,
V.Z.


.

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