- #1
monicamlmc
- 1
- 0
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!
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!