By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

A python package for penalized generalized linear models that supports fitting and model selection for structured, adaptive and non-convex penalties.

A workshop on using generalized additive models and the mgcv package.

Penalized least squares estimation using the Orthogonalizing EM (OEM) algorithm

FAST Change Point Detection in R

A Julia module that implements the (normalized) iterative hard thresholding algorithm(IHT) of Blumensath and Davies. IHT performs feature selection akin to LASSO- or MCP-penalized regression using a greedy selection approach.

Nonparametric regression and prediction using the highly adaptive lasso algorithm

Variable selection for heterogeneous populations using the vennLasso penalty

Penalized Regression with Second-Generation P-Values

LASSOPACK: Stata module for lasso, square-root lasso, elastic net, ridge, adaptive lasso estimation and cross-validation

Source files for R package Sieve

Network-Based Regularization for Generalized Linear Models

Biomarker selection in penalized regression models

Regression models for "epigenetic clock" estimation of canine chronological age

Supplementary material for the medium article Beyond linear regression: Leveraging linear regression for feature selection of continuous/categorical variables.

CRAN R package - oscar: Optimal Subset CArdinality Regression models

We explored various approaches to deal with high-dimensional data in this study, and we compared them using simulation and soil datasets. We discovered that grouping had a significant impact on model correctness and error reduction. For the core projection step, we first looked at the properties of all the algorithms and how they function to com…

Experiments for Binarsity: a penalization for one-hot encoded features

Raw files for a document providing an overview of mixed models from varying perspectives.

Flexible SVM framework implementation