Package: HMMpa 1.0.2

Foraita Ronja

HMMpa: Analysing Accelerometer Data Using Hidden Markov Models

Analysing time-series accelerometer data to quantify length and intensity of physical activity using hidden Markov models. It also contains the traditional cut-off point method. Witowski V, Foraita R, Pitsiladis Y, Pigeot I, Wirsik N (2014). <doi:10.1371/journal.pone.0114089>.

Authors:Vitali Witowski [aut], Foraita Ronja [cre, aut]

HMMpa_1.0.2.tar.gz
HMMpa_1.0.2.zip(r-4.5)HMMpa_1.0.2.zip(r-4.4)HMMpa_1.0.2.zip(r-4.3)
HMMpa_1.0.2.tgz(r-4.5-any)HMMpa_1.0.2.tgz(r-4.4-any)HMMpa_1.0.2.tgz(r-4.3-any)
HMMpa_1.0.2.tar.gz(r-4.5-noble)HMMpa_1.0.2.tar.gz(r-4.4-noble)
HMMpa_1.0.2.tgz(r-4.4-emscripten)HMMpa_1.0.2.tgz(r-4.3-emscripten)
HMMpa.pdf |HMMpa.html
HMMpa/json (API)
NEWS

# Install 'HMMpa' in R:
install.packages('HMMpa', repos = c('https://bips-hb.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bips-hb/hmmpa/issues

On CRAN:

Conda:

accelerometer-datahidden-markov-modeltime-series

3.18 score 1 packages 660 downloads 16 exports 0 dependencies

Last updated 2 months agofrom:7f2ddcc4d8. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 05 2025
R-4.5-winOKMar 05 2025
R-4.5-macOKMar 05 2025
R-4.5-linuxOKMar 05 2025
R-4.4-winOKMar 05 2025
R-4.4-macOKMar 05 2025
R-4.4-linuxOKMar 05 2025
R-4.3-winOKMar 05 2025
R-4.3-macOKMar 05 2025

Exports:AIC_HMMBaum_Welch_algorithmBIC_HMMcut_off_point_methoddgenpoisdirect_numerical_maximizationforward_backward_algorithmHMM_based_methodHMM_decodingHMM_simulationHMM_traininginitial_parameter_traininglocal_decoding_algorithmpgenpoisrgenpoisViterbi_algorithm

Dependencies: