Analysing Accelerometer Data Using Hidden Markov Models

Documentation for package ‘HMMpa’ version 1.0.1

HMMpa-package	Analysing Accelerometer Data Using Hidden Markov Models
AIC_HMM	AIC and BIC Value for a Discrete Time Hidden Markov Model
Baum_Welch_algorithm	Estimation Using the Baum-Welch Algorithm
BIC_HMM	AIC and BIC Value for a Discrete Time Hidden Markov Model
cut_off_point_method	Cut-Off Point Method for Assigning Physical Activity Patterns
dgenpois	The Generalized Poisson Distribution
direct_numerical_maximization	Estimation by Directly Maximizing the log-Likelihood
forward_backward_algorithm	Calculating Forward and Backward Probabilities and Likelihood
HMMpa	Analysing Accelerometer Data Using Hidden Markov Models
HMM_based_method	Hidden Markov Method for Predicting Physical Activity Patterns
HMM_decoding	Algorithm for Decoding Hidden Markov Models (local or global)
HMM_simulation	Generating Realizations of a Hidden Markov Model
HMM_training	Training of Hidden Markov Models
initial_parameter_training	Algorithm to Find Plausible Starting Values for Parameter Estimation
local_decoding_algorithm	Algorithm for Decoding Hidden Markov Models (local)
pgenpois	The Generalized Poisson Distribution
rgenpois	The Generalized Poisson Distribution
Viterbi_algorithm	Algorithm for Decoding Hidden Markov Models (global)