All three of your models: Exponential, Gamma and Weibull are of the form a*X^s where X is Gamma with n degrees of freedom and s and a are additional unknown parameters.
For n=s=1 we have exponential. For s=1 we have gamma. For n=1 we have Weibull. Thus fit a*X^s and use the likelihood ratio test to test specific submodels. You can generalize this further to a generalized F if you like. See http://www.math.mun.ca/~ypeng/research.html . "Chia C Chong" <[EMAIL PROTECTED]> wrote in message news:<a0v9sk$j7j$[EMAIL PROTECTED]>... > Hi!! > > I have a set of data with some kind of distribution. When I plotted the > histogram density of this set of data, it looks sth like the > Weibull/Exp/Gamma distribution. I find the parameters that best fit the data > and then, plot the respective distribution using the estimated parameters on > the empirical distribution. My question is, what kind of statistical test > that I should use so that I will know which estimated distribution will fit > the data better?? I need some kind of test that will give me some numerical > values which distribution is fit better rather than just observed the > fitting graphically.. > > Thanks for th help in advance.. > > Regards, > CCC ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =================================================================
