# Fisher Scoring v/s Coordinate Descent for MLE in R

R base function glm() uses Fishers Scoring for MLE, while the glmnet appears to use the coordinate descent method to solve the same equation. Coordinate descent is more time-efficient than Fisher Scoring, as Fisher Scoring calculates the second order derivative matrix, in addition to some other matrix operations. which makes expensive to perform, while coordinate descent can do the same task in O(np) time.

Why would R base function use Fisher Scoring? Does this method have an advantage over other optimization methods? How does coordinate descent and Fisher Scoring compare? I am relatively new to do this field so any help or resource will be helpful.