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Thread Subject:
How to make a Maximum Likelihood estimation in matlab

Subject: How to make a Maximum Likelihood estimation in matlab

From: Alex

Date: 18 May, 2011 15:53:04

Message: 1 of 4

Dear all,
I would like to have MLE in Matlab.
Could you please help me by specifing a good starting point?

I would like to thank you in advance for your help

Best Regards
Alex

Subject: How to make a Maximum Likelihood estimation in matlab

From: Florin Neacsu

Date: 18 May, 2011 16:44:04

Message: 2 of 4

"Alex " <alaios@yahoo.com> wrote in message <ir0q10$9r$1@newscl01ah.mathworks.com>...
> Dear all,
> I would like to have MLE in Matlab.
> Could you please help me by specifing a good starting point?
>
> I would like to thank you in advance for your help
>
> Best Regards
> Alex

Hello,

If you understand what MLE is and does you can implement the algorithm yourself.
You can also use our friend google/bing/yahoo ... and look for an implementation (matlab or not) and then rewrite it in matlab. Also, if you have the statistic toolbox, I believe the is a function called mle which probably suits your needs.

Regards,
Florin

Subject: How to make a Maximum Likelihood estimation in matlab

From: Alex

Date: 19 May, 2011 08:39:03

Message: 3 of 4

Thank you very much for your reply.

Actually I have to try to fit some value that I believe mostly follow the following function

y= constant+ 10*log10(x).

Can you help me understand a bit of theory how I can do that in matlab?

Best Regards
Alex

Subject: How to make a Maximum Likelihood estimation in matlab

From: Tom Lane

Date: 19 May, 2011 14:06:31

Message: 4 of 4

> Actually I have to try to fit some value that I believe mostly follow the
> following function
>
> y= constant+ 10*log10(x).
>
> Can you help me understand a bit of theory how I can do that in matlab?

Alex, if the constant is all you need, and if y has a normal distribution
for a given x value:

>> x = rand(100,1);
>> y = normrnd(5 + 10*log10(x),.1);
>> mean(y-10*log10(x))
ans =
       4.9933

If you need to estimate the 10 also:

>> polyfit(log10(x),y,1)
ans =
       9.9817 4.9856

If you need something more elaborate, perhaps you can explain what that is.

--Tom

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