# 'mle' - can we use this command for maximizing log-likelihood estimation of a vector input, which is normally distributed?

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### Answers (1)

Mayank Sengar
on 30 Aug 2022

##### 2 Comments

Torsten
on 7 Sep 2022

Edited: Torsten
on 7 Sep 2022

You have data from which you assume that they follow a normal distribution with mean mu and standard deviation sigma. Now you want to estimate mu and sigma for your data. For this, you use "mle" and you get the estimated parameters mu and sigma in return. The method to determine them is to maximize the log likelihood function. In order to get the maximum value of this function, you can use "negloglik" on the result obtained from "fitdist". "fitdist" can be used alternatively to "mle" to estimate your distribution parameters.

If you still don't understand the concept, you should consult Wikipedia before asking permanently the same questions.

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