SiER
0.1.0Signal Extraction Approach for Sparse Multivariate Response Regression
Overview
Methods for regression with high-dimensional predictors and univariate or maltivariate response variables. It considers the decomposition of the coefficient matrix that leads to the best approximation to the signal part in the response given any rank, and estimates the decomposition by solving a penalized generalized eigenvalue problem followed by a least squares procedure. Ruiyan Luo and Xin Qi (2017) doi:10.1016/j.jmva.2016.09.005.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-03-109 OK · 5 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
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- References docs
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1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2017-09-19
- Total releases
- 1 / 9 yrs
- License
- GPL-2 OSI
- Download size
- 7.4 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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