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FITMETHIS finds best-fitting distribution to data vector



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F= fitmethis(X) finds the distibution that best fits data in vector X among all distributions available in MATLAB's function MLE. Either continuous or discrete distributions are used based on user input or the type of data supplied (see below) The function returns a structure array with fields:
name: name of the distribution (see HELP MLE for a list)
par: vector of parameter estimates (1, 2 or 3 values)

ci: matrix of confidence limits, one column per parameter

LL: Log-Likelihood of the data

aic: Akaike Information Criterion

Optional arguments can be specified as name/value pairs (see help).

Comments and Ratings (5)

Radek Silhavy

This nice code, How to resolve the which distribution was the best?

moatez hassan

I am interesting to use lines of code in my work

Hoped to use, however, after just a first trial, encountered some confusions starting from: the MATLAB GEV version is for maxima, the MATLAB EV version is for minima, so to match between them, your must mirror either GEV or EV. You may compare the location parameter you get for GEV as is with the location parameter you get for EV as is. They are a great deal different. A simple solution for this case is mirroring EV by negating the input, i.e. by using "-x" instead of "x" and then mirroring the EV location parameter by negating it. In this way, you will come much closer to the GEV location parameter.

Nice piece of work.I am so thankful to you as this code has solved much of my research work.The problem is, I also wanna find out the mean and SD of that distribution.So how could I do that?

I didn't realize there was already a function to do this (more comprehensive, probably): ALLFITDIS by Mike Sheppard.



Better handling of preferred distribution in FITMETHIS. Better plot of discrete distributions in PLOTFITDIST


Better handling of preferred distribution


Modify helper function plotfitdist.m

MATLAB Release
MATLAB 8.0 (R2012b)

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