Normally one would fit a distribution in the Pearson systme by moments, so using MEAN, STD, SKEWNESS, and KURTOSIS (the latter two in the Statistics Toolbox) can be used to do this.
The Pearson Type III is a simple transformation of the gamma distrinution, and the PEARSRND function can be used to find the coefficients. Then look at the code in PEARSRND to get the actual transformation that you'd use along with GAMCDF to compute values from the Pearson Type III CDF.
This all assumes you want to fit a distribution to univariate data, not fit a regression curve to bivariate data.
On 10/10/2013 11:26 AM, Poulomi wrote: > "Poulomi" wrote in message <firstname.lastname@example.org>... >> Hi, >> >> I want to fit pearson type 3 CDF to monthly precipitation data. I >> didn't found any function perscdf in MATLAB. Let me know how can I fit >> Pearson CDF to my data. Thanks, > > I want to estimate parameters of the distribution too.., thanks,