[ rearranging to the usual order, with Reply at the bottom ] > Chia C Chong wrote: > > > > 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 ... [ ... ]
On 14 Jan 2002 08:15:35 -0800, [EMAIL PROTECTED] (kjetil halvorsen) wrote: > A quantile-Quantile plot for graphical comparison is best, if you need a > numerical test you can use the pearson correlation coefficient between > the observed and expected quantiles. A table for that test you can ake > for yourself with simulation. No, I think that advice is not good, in this instance. Someone else has mentioned that these three belong to the same family so that it is possible and most desirable to solve for the value of the parameter that distinguishes them. The correlation between those 'quantiles' -- That (I think) gets you a test like the Shapiro-Wilks which is a fine test for normality when you compare correlations across a range of deviant samples. I don't remember its analog being used for testing between theoretical CDFs; and I suspect it is inferior to other approaches for (say) strongly skewed distributions. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =================================================================
