Generative-model-free likelihood

R-bloggers 2021-01-21

Summary:

This post is a follow-up of my previous post on the likelihood principle and model evaluation. This time I would like to start by a more practical angle: Many ML methods are mode-based-optimization: we are given an objective function f(theta, y) and we will solve theta by the mode. It is tempting to convert this […]

Link:

https://statmodeling.stat.columbia.edu/2020/12/30/generative-model-free-likelihood/

From feeds:

Statistics and Visualization » Statistical Modeling, Causal Inference, and Social Science

Tags:

bayesian

Authors:

Yuling Yao

Date tagged:

01/21/2021, 22:57

Date published:

12/30/2020, 16:00