This project aims to explore empirical Bayes multiple regression methods.
Here is a collection of occassional unrefined Jupyter Notebooks from my daily work,
with a lazy attempt to categorize
For my other notebook collections, visit here.
Optmization of the penalty function using Lagrange multiplier
Jan 10, 2022
Comparison of Lasso from R (glmnet) and Python (sklearn)
Sep 20, 2021
Peter's example of varbvs surface visualization
Sep 16, 2021
Illustration of Mr.ASH and Mr.ASHPen on some special cases
Sep 13, 2021
Demonstration of Mr.ASH penalized regression
Aug 24, 2021
Mr.ASH penalized regression trendfiltering demo
Jun 15, 2021
Comparison of different methods for changepoint estimation
Apr 12, 2021
Demonstration of EM-VAMP with changepoint simulation
Apr 9, 2021
Demonstration of EM-VAMP with adaptive shrinkage (ash) prior
Mar 31, 2021
Comparison of prediction accuracy of EM-VAMP, Mr.ASH and EBMR
Mar 29, 2021
Comparison of prediction accuracy of linear regression methods
Mar 24, 2021
Multiple regression with product of normals
Feb 19, 2021
Multiple regression (two predictors) with product of normals
Jan 28, 2021
Simple regression with product of normals
Jan 27, 2021
Effect of σb and σw in EBMR with product of normals
Jan 11, 2021