spar: Sparse Projected Averaged Regression in R

TL;DR

The spar package for R introduces an efficient ensemble method for high-dimensional generalized linear models using variable screening and random projections, emphasizing extensibility and user customization.

Contribution

It provides a flexible, extensible framework with S3 classes for integrating screening and projection techniques in high-dimensional regression modeling.

Findings

Efficient handling of large predictor sets.

Flexible design with user-friendly extension capabilities.

Applicable to various high-dimensional applications.

Abstract

Package spar for R builds ensembles of predictive generalized linear models with high-dimensional predictors. It employs an algorithm utilizing variable screening and random projection tools to efficiently handle the computational challenges associated with large sets of predictors. The package is designed with a strong focus on extensibility. Screening and random projection techniques are implemented as S3 classes with user-friendly constructor functions, enabling users to easily integrate and develop new procedures. This design enhances the package's adaptability and makes it a powerful tool for a variety of high-dimensional applications.