Log likelihood
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Hi!
I was wondering how to compute (which function to use) in Matlab the log likelihood but when the data is not normally distributed. Thanks!
Nuchto
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Tom Lane
2012년 5월 24일
If you have the most recent release of the Statistics Toolbox:
>> x = poissrnd(4,20,1);
>> pd = fitdist(x,'poisson');
>> pd.NLogL
ans =
39.0221
If you do not:
>> mu = poissfit(x);
>> -sum(log(poisspdf(x,mu)))
ans =
39.0221
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Tom Lane
2012년 5월 29일
Sadly, it doesn't say much on its own. You could compare it to the likelihood of other fits.
Jessica Hopf
2023년 3월 3일
Im curious where the documentation for pd.NLogL is? specifically, I can't find how you would know to do this without having found this answer
추가 답변 (2개)
the cyclist
2012년 5월 22일
편집: John Kelly
2015년 2월 26일
If you have the Statistics Toolbox, you can calculate the (negative) log likelihood for several functional forms.
For example, there is a betalike() function that will calculate the NLL for a beta function.
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the cyclist
2012년 5월 23일
I'm not sure I understand what you mean. When you say you can't "find" them, do you mean they are not in your version of MATLAB? Do you have the Statistics Toolbox?
Or do you mean that you see all those functions, but none of them are for the distribution you are trying to use?
Or do you mean something else?
Oleg Komarov
2012년 5월 24일
You can try the following submission: http://www.mathworks.co.uk/matlabcentral/fileexchange/34943-fit-all-valid-parametric-probability-distributions-to-data
It will fit several distributions and should return the NLL (NegLogLik) for each.
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