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krm

2022.10-17Package record

Kernel Based Regression Models

0packages depend
2.9Kdownloads / year
38.8%test coverage
13/13flavors OK

Overview

About

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

CRAN checks
13OK
Slowest check: 2.8 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 2022.10-17
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
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

2.9K
CRAN downloads in the past year
Rank #9,531 · ~8/day · ~243/mo
Daily download trend is not available in this view yet.
35030 days
1K90 days
2.9K1 year
Compare downloads with other packages →
Also on363 r2u6 autocran55 c2d4u

Dependencies

Declared dependencies
2 external dependencies (excludes base and recommended)

Installing krm adds 1 package (1 with compiled code, 209 KB of source tarballs). Heaviest: kyotil 209 KB.

Depends (2)
R >= 3.3.0kyotil
Imports (1)
methods
LinkingTo (0)
none
Suggests (2)
RUnitMASS
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (5)
Maintainer since 13.10-31 (2013)
Contributor · added in 2018.1-24
Contributor · added in 2018.1-24
Releases (10)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • 2022.10-17Latest
    record
    2022-10-18 · current release · diff ↗
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • 2020.5-20
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    2020-05-21 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • 2019.12-11
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    2019-12-10 · diff ↗
  • R
    R 3.6.0 released · 2019-04-26
  • 2018.8-17
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    2018-08-18 · diff ↗
  • R
    R 3.5.0 released · 2018-04-23
  • 2018.1-24
    record
    2018-01-24 · diff ↗
  • R
    R 3.4.0 released · 2017-04-21
  • 2016.7-9
    record
    2016-07-10 · diff ↗
Show 8 earlier eventsHide 8 earlier events
  • R
    R 3.3.0 released · 2016-05-03
  • R
    R 3.2.0 released · 2015-04-16
  • 2015.3-4
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    2015-03-04 · diff ↗
  • 2014.12-1
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    2014-12-02 · diff ↗
  • R
    R 3.1.0 released · 2014-04-10
  • 13.11-03
    record
    2013-11-05 · diff ↗
  • 13.10-31
    record
    2013-11-03
  • R
    R 3.0.0 released · 2013-04-03

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")
Fong, Y., Datta, S., Geyer, D., Park, S., & Sebestyen, K. (2022). krm: Kernel Based Regression Models (Version 2022.10-17) [Computer software]. https://doi.org/10.32614/CRAN.package.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.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for krm version 2022.10-17 [Data set]. HJJB, LLC. Data release v2026-10-19. https://doi.org/10.5281/zenodo.21843040

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.

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