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HMMpa
View on CRAN: Click
here
Download and install HMMpa package within the R console
Install from CRAN:
install.packages("HMMpa")
Install from Github:
library("remotes")
install_github("cran/HMMpa") Install by package version:
library("remotes")
install_version("HMMpa", "1.0.2") Attach the package and use:
library("HMMpa")
Maintained by
Ronja Foraita
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-02-25
Latest Update: 2025-01-31
Description:
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).
How to cite:
Ronja Foraita (2014). HMMpa: Analysing Accelerometer Data Using Hidden Markov Models. R package version 1.0.2, https://cran.r-project.org/web/packages/HMMpa. Accessed 26 Oct. 2026.
Previous versions and publish date:
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Other R packages that HMMpa depends,
imports, suggests or enhances
Complete documentation for HMMpa
Functions, R codes and Examples using
the HMMpa R package
Some associated functions: AIC_HMM . Baum_Welch_algorithm . HMM_based_method . HMM_decoding . HMM_simulation . HMM_training . HMMpa-package . Viterbi_algorithm . cut_off_point_method . dgenpois . direct_numerical_maximization . forward_backward_algorithm . initial_parameter_training . local_decoding_algorithm .
Some associated R codes: AIC_HMM.R . BIC_HMM.R . Baum_Welch_algorithm.R . HMM_based_method.R . HMM_decoding.R . HMM_simulation.R . HMM_training.R . Viterbi_algorithm.R . cut_off_point_method.R . dgenpois.R . direct_numerical_maximization.R . forward_backward_algorithm.R . initial_parameter_training.R . local_decoding_algorithm.R . pgenpois.R . rgenpois.R . Full HMMpa package functions and examples
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