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RcppHMM

1.2.2.1Package record

Rcpp Hidden Markov Model

0packages depend
3.1Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Collection of functions to evaluate sequences, decode hidden states and estimate parameters from a single or multiple sequences of a discrete time Hidden Markov Model. The observed values can be modeled by a multinomial distribution for categorical/labeled emissions, a mixture of Gaussians for continuous data and also a mixture of Poissons for discrete values. It includes functions for random initialization, simulation, backward or forward sequence evaluation, Viterbi or forward-backward decoding and parameter estimation using an Expectation-Maximization approach.

Install

Health

CRAN checks
13OK
Slowest check: 4.0 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK12 OK2026-04-25
  • NOTE13 OK, 1 NOTE2026-04-22
  • ERROR12 OK, 1 NOTE, 1 ERROR2026-04-18
Show 1 earlier changeHide 1 earlier change
  • NOTE13 OK, 1 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.2.2.1
READMENoVignettesNoNEWSYes · 0% structuredCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
14includes a package overview page
Examples that run
100%13 run in a plain check
Exported functions with examples
93%
Documented parameters
not tracked
Return-value docs
not tracked
Help pages citing references
64%

Downloads

3.1K
CRAN downloads in the past year
Rank #14,703 · ~8/day · ~258/mo
Daily download trend is not available in this view yet.
28730 days
82690 days
3.1K1 year
Compare downloads with other packages →
Also on344 r2u6 autocran

Dependencies

Declared dependencies
3 external dependencies (excludes base and recommended)

Installing RcppHMM adds 2 packages (2 with compiled code, 2.8 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB.

Depends (0)
none
Imports (1)
LinkingTo (2)
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (3)
Author, Maintainer since 1.0.1 (2017)
Author · added in 1.2
Author · added in 1.2
Listed in earlier versions (1)
Cardenas-Ovando
no longer listed · 1.2.2.1
Releases (4)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.2.2.1Latest
    record
    2025-09-18 · current release · diff ↗
  • 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
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • 1.2.2
    record
    2017-11-21 · diff ↗
  • 1.2
    record
    2017-08-30 · diff ↗
  • R
    R 3.4.0 released · 2017-04-21
  • 1.0.1
    record
    2017-02-08
  • R
    R 3.3.0 released · 2016-05-03

Package metadata

First published
2017-02-08
Total releases
4 / 9 yrs
License
GPL (>= 3) OSI
Download size
30 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("RcppHMM")
Cardenas-Ovando, R. A., Noguez, J., & Rangel-Escareno, C. (2025). RcppHMM: Rcpp Hidden Markov Model (Version 1.2.2.1) [Computer software]. https://doi.org/10.32614/CRAN.package.RcppHMM

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 RcppHMM version 1.2.2.1 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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