Publication | Open Access
<b>lmSubsets</b>: Exact Variable-Subset Selection in Linear Regression for <i>R</i>
18
Citations
20
References
2020
Year
R PackageEngineeringHigh-dimensional MethodData ScienceData MiningPredictive AnalyticsFeature SelectionExact Variable-subset SelectionStatistical InferenceAll-subsets Regression ProblemStatistical Learning TheoryStatisticsBest-subset Regression Problem
An R package for computing the all-subsets regression problem is presented. The proposed algorithms are based on computational strategies recently developed. A novel algorithm for the best-subset regression problem selects subset models based on a predetermined criterion. The package user can choose from exact and from approximation algorithms. The core of the package is written in C++ and provides an efficient implementation of all the underlying numerical computations. A case study and benchmark results illustrate the usage and the computational efficiency of the package.
| Year | Citations | |
|---|---|---|
Page 1
Page 1