Kernel Based Regression Models
Overview
Implements several methods for testing the variance component parameter in regression models that contain kernel-based random effects, including a maximum of adjusted scores test. Several kernels are supported, including a profile hidden Markov model mutual information kernel for protein sequence. This package is described in Fong et al. (2015) DOI:10.1093/biostatistics/kxu056.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 12
- Examples that run
- 75%3 run in a plain check · 1 never run
- Exported functions with examples
- 44%
- Documented parameters
- 98%
- Return-value docs
- 33%
- Help pages citing references
- 8%
Downloads
Dependencies
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 2022.10-17Latest
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 2020.5-202020-05-21 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 2019.12-112019-12-10 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 2018.8-172018-08-18 · diff ↗
- RR 3.5.0 released · 2018-04-23
- 2018.1-242018-01-24 · diff ↗
- RR 3.4.0 released · 2017-04-21
- 2016.7-92016-07-10 · diff ↗
Package metadata
- First published
- 2013-11-03
- Total releases
- 10 / 13 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.3.0
- Bundled data
- 2.8 KB / 2 files
- Download size
- 44 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("krm")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.