Package: HMMpa 1.0.1

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, Ronja Foraita

HMMpa_1.0.1.tar.gz
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HMMpa.pdf |HMMpa.html
HMMpa/json (API)

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

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

16 exports 0.36 score 0 dependencies 1 dependents 26 scripts 246 downloads

Last updated 6 years agofrom:d8aa5cfb92. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 14 2024
R-4.5-winOKSep 14 2024
R-4.5-linuxOKSep 14 2024
R-4.4-winOKSep 14 2024
R-4.4-macOKSep 14 2024
R-4.3-winOKSep 14 2024
R-4.3-macOKSep 14 2024

Exports:AIC_HMMBaum_Welch_algorithmBIC_HMMcut_off_point_methoddgenpoisdirect_numerical_maximizationforward_backward_algorithmHMM_based_methodHMM_decodingHMM_simulationHMM_traininginitial_parameter_traininglocal_decoding_algorithmpgenpoisrgenpoisViterbi_algorithm

Dependencies: