A good tool for realizing qq-plot in "machine learning" matlab gqqplot_ machine learning

A good tool to realize qq-plot in MATLAB gqqplot June June 26, 2013

These days looked at Qq-plot as well as in the implementation of MATLAB, but the qqplot function of Matlab can not meet my use, so search on the Internet a good tool: Gqqplot. Gqqplot can be compared to many common distributions, while Qqplot can only compare normal distribution. Its zip file download link: gqqplot

Gqqplot Description:

Gqqplot (x,dist) makes an plot of the quantiles of the data set X versus the inverse of the ' cdf of a distribution specified In DIST, evaluated at probabilities equal to the quantiles of X. The parameters of the distribution are calculated from X.

The purpose of the QQ plot is to determine whether the "sample in" X is drawn from given distribution. If It is, the plot'll be linear. In the case of the binomial distribution, a additional parameter is needed:n, number of trials, e.g. Gqqplot (X, ' binom ', N ).

The name of the distribution can is (case insensitive):

' Norm ' or ' normal '
' Gam ' or ' gamma '
' Logn ' or ' lognormal ',
' Exp ' or ' exponential ',
' WBL ' or ' Weibull '.
' Beta '
' Bin ' or ' binomial '
' EV ' or ' Extreme Value ',
' GeV ' or ' Generalized Extreme Value ',
' GP ' or ' Generalized Pareto ',
' Nbin ' or ' Negative binomial ',
' Poiss ' or ' Poisson '
' unif ' or ' uniform '
' Rayl ' or ' Rayleigh '

Example:1 2 3 x= gamrnd (2,0.5,1000,1); Gqqplot (x, ' normal ')%bad fit Gqqplot (x, ' gamma ')%good fit