Re: [R] Fisher Scoring v/s Coordinate Descent for MLE in R

There are books on this, can't repeat them here... Roughly speaking, Fisher Scoring is quadratically convergent, hence requires much fewer iterations than gradient descent methods which are generally only linear, and sometimes very slowly so (in highly collinear cases, usually). I.e., it is a

[R] Fisher Scoring v/s Coordinate Descent for MLE in R

R base function glm() uses Fishers Scoring for MLE, while the glmnet uses 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 and some other matrix operation which