Studying machine learning and statistical pattern recognition these days, I’ve learned a nice fact about estimation. The proof is straightforward but I’d like to remeber this fact, so here it is.
Let and let follow a normal gaussian distribution .
In a least squares estimate one minimize the following
In a maximum likelihood one defines a likelihood
and then minimize
which is equivalent to (*). QED