Gamma and Weibull location parameter estimation

AI Thread Summary
The discussion focuses on estimating the location parameters for three-parameter Weibull and Gamma distributions using a direct method, as the user seeks to enhance their probability distribution analysis. They are currently employing the Kolmogorov-Smirnov test for goodness-of-fit on various distributions but prefer to avoid iterative methods due to speed concerns. A suggestion is made to utilize MATLAB's Statistical toolkit, which provides estimators for these distributions, allowing for parameter fitting directly from raw data. The user expresses a limited background in statistics, indicating a need for straightforward solutions. Overall, the conversation highlights the challenge of parameter estimation in statistical modeling while seeking efficient methods.
monicamlmc
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Hi all,

I have a set of samples and I would like to detect the probability distribution that best represents the data. I'm using the kolmogorov-Smirnov test to verify the goodness-of-fit for some well-known distributions, like Gamma, exponential and Weibull. Since I don't know the distribution parameters, I'm estimating them (using the mechanism of rank regression on Y in most cases).

My problem is that I need to extend my set of tested distributions adding the three-parameter weibull and three-parameter gamma distributions. However, I can't find a "direct" method to estimate the location parameter for both distributions. By "direct" I mean some closed formula. I found some iterative methods, but I'm trying to avoid them because speed of detection is a very important factor in my work. Btw, I'm a Computer Science student, I have a very limited background in statistics... :-( may be what I want to do is not possible, I don't know...

Can anyone help me?

Thanks in advance!
 
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Matlab's Statistical toolkit has estimators for these distributions. I've used the Weibull one, can't remember if it does all three parameters. You input the raw data and it gives you parameter fits.
 
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