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-4.7)HMMpa_1.0.2.zip(r-4.6)HMMpa_1.0.2.zip(r-4.5)
HMMpa_1.0.2.tgz(r-4.6-any)HMMpa_1.0.2.tgz(r-4.5-any)
HMMpa_1.0.2.tar.gz(r-4.7-any)HMMpa_1.0.2.tar.gz(r-4.6-any)
HMMpa_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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

3.99 score 1 packages 65 scripts 309 downloads 16 exports 0 dependencies

Last updated from:7f2ddcc4d8. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK121
source / vignettesOK191
linux-release-x86_64OK114
macos-release-arm64OK63
macos-oldrel-arm64OK97
windows-develOK81
windows-releaseOK115
windows-oldrelOK65
wasm-releaseOK87

Exports:AIC_HMMBaum_Welch_algorithmBIC_HMMcut_off_point_methoddgenpoisdirect_numerical_maximizationforward_backward_algorithmHMM_based_methodHMM_decodingHMM_simulationHMM_traininginitial_parameter_traininglocal_decoding_algorithmpgenpoisrgenpoisViterbi_algorithm

Dependencies: