Generalized Linear Models: Likelihood, Score, and Fisher Information скачать в хорошем качестве

Generalized Linear Models: Likelihood, Score, and Fisher Information

Error: Many thanks to @joshdavis5224 for finding and noting an error in this video. Equation (4) at 5:17 does not make sense. If we are taking the derivative of L with respect to theta_i then we should lose the summation. Since for each j not equal to i, the contribution to the sum should be constant. Again, many thanks for bringing this to my attention. In this video we are building up to the Iteratively Reweighted Least Squares Regression for the GLM model. A small note. When I write the Fisher Information in matrix form, the equal sign in front shouldn't be there. Here is the link to my playlist Generalized Linear Models    • Generalized Linear Models   Help this channel to remain great! Donating to Patreon or Paypal can do this!   / statisticsmatt   https://paypal.me/statisticsmatt