Using maximum likelihood estimate

I've been struggling for a long time now to use MLE for a project I am doing. It's about modelling motor activity in Mice. Basically I have two variables... one is a long list of values for motor activity for Mouse 1 and then other is the same for Mouse 2.

I have them modeled as follows using hist(data), hold all; hist(data2) then changing the Y axis to log and X stays linear.

My problem is, I have no idea how to fit an MLE line down the data... Like I know it needs to intersect at various points and run as a diagonal line the length of the data but I don't know how.

I've tried phat = mle (data) and I get a variable called mle. then when I plot (mle) I get a tiny diagonal line which is no good to me.

Sorry if what i'm saying is hard to understand but this (hopefully) simple matter is the key to me completing this project.

Thanks for taking the time to read!

Answer 1

[Star Strider]

Have you explored histfit? It might be what you want.

[Star Strider]

It doesn’t say specifically in the histfit documentation (I looked before I posted this), but on the basis of the other distribution fitting functions I would assume so. It probably is a function that does its best to make life easier by creating and fitting the histogram in one command.

Answer 2

[harry]

interesting this may be what i'm looking for. Do you know if this can be used to fit Maximum likelihood estimation?