Try to make a fitting for my data distribution
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Dear ALL
I have a problem on the fitting for my data, let me explain:-
i have my data, i call it (y), y is matrix its size= 1 X 64809
I am looking for the best distribution by using dfittool ( i don't know whether this tool is good or not). So,this tool gives me that the best one is t location-scale with the parameters ( mu=0.000346043,sigma=0.00195851 and degree of freedom=0.882799),please see this figure https://www.dropbox.com/s/976xiawizx4qvma/2.jpg.
After all, i generat a random number matrix ( X ) with same size of y-matrix (size= 1 X 64809) and withe the same t location-scale parameters, by using the folowing functions:-
dist = ProbDistUnivParam('tlocationscale',[0.000346043,0.00195851,0.882799]);
X=random(dist,1,length(y)); % the random number matrix
Now , to check whether my distribution is fitted my data or not, i used a qqplot fnction as
qqplot(X,y).
So, the question is, why the two distrbuation is not similar?? and why there is not matching?
please help me, and if any one need my data i can send him to help me on the fitting distribution.
Thanks in advance
2 Comments
Frank
on 22 May 2023
Although I cannot access your picture attachments but I believe I encountered the same problem, could you tell me have you sorted this problem out? And how to sort it out?
Answers (2)
Wayne King
on 22 Dec 2012
It looks to me like the problem you are seeing in the qqplot() is that your selection of the generalized t-distribution (t location-scale) results in a distribution with tails much wider than the vary narrow range of your Y data. For example, look at the PDF
xval = -2:.01:2;
y = pdf(ProbDistUnivParam('tlocationscale',[0.000346043,0.00195851,0.882799]),xval);
plot(xval,y,'linewidth',2); set(gca,'ylim',[-0.5 max(y)]);
If you look at your random vector generated from this PDF, obviously the qqplot looks good
L = 64809;
X = random(dist,1,L);
qqplot(X,dist)
but your actual data does not match the long-tailed behavior of the t location scale density even though the match in the center of the distribution is good.
The smaller the number of degrees of freedom in a t location-scale family PDF, the heavier the tails.
It's not that dfittool is not a good tool, it is a fine tool. It's just in this case either a different option would give a better fit, or perhaps a PDF not supported by dfittool.
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