Maximum Likelihood estimators of simple linear regression weights

Hi, Sorry if this question is too simple. I am new to matlab and statistics aswell. I have a to train a simple linear regression model which has n features. This means that I have to calculate n weights for the features. So what I need to ask is that how can I calculate the maximum likelihood estimators of the weights in matlab.

Thanks

Answer 1

[Image Analyst]

Try polyfit().

[Tom Lane]

Or backslash or a Statistics Toolbox function such as regress, if n represents the number of columns in your matrix of features. These yield least squares estimates, which are the maximum likelihood estimators if the output (response) has a normal distribution.