# Why is Fisher Scoring easier to compute?

In practice, the observed information matrix (Newton-Raphson) is usually replaced by its expectation, known as Fisher scoring.

What I don't understand is, why the expectation of the matrix is easier to compute than the matrix itself? Otherwise, there wouldn't be any point to use Fisher scoring.

• Because you only need to take the first (not the second) derivatives, which can be expressed as the expectation. – Randel Oct 7 '15 at 14:31
• @Randel Can you elaborate a bit more? Other users might also find your answer helpful. Most textbooks don't say why Fisher scoring is better computationally. – SmallChess Oct 7 '15 at 14:33
• I would refer to Page 88, Section 2.11.2 Empirical FS algorithm of the book by Prof. Demidenko. This is the FS algorithm I usually see, and there are some approximation. – Randel Oct 7 '15 at 23:53