Package index • autoregressivehmm

All functions

allprobs(): Matrix of all probabilities

ar_simulation(): Simulation of autoregressive HMMs

autoregressivehmm-package autoregressivehmm: Autoregressive HMMs: To give all this code some structure

boxplot_params(): Boxplot of different simulation runs

boxplot_sim_params(): Full simulation boxplots of estimated parameters

circ_vm_viz(): Circular KDE and density of von Mises distribution

dens_gamma(): Density of gamma distribution

dens_norm(): Density of normal distribution

dens_vm(): Density of von Mises distribution

fit_arp_model(): Fit an autoregressive HMM to data

full_sim_loop(): Simulation loop

logAlpha(): Forward log-probabilities

mllk(): Compute negative (penalized) log-likelihood of an autoregressive HMM

nice_params(): Construct parameter object for autoregressive HMM likelihood evaluation

plot_data(): Plot data

plot_decoded_data(): Plot decoded data

plot_fitted_dist(): Density plot of estimated distributions of autoregressive HMMs

plot_states(): Plot states decoded by Viterbi algorithm

pseudores_arp(): Compute pseudo residuals

sample_arp(): Simulate data from an autoregressive HMM

sample_gamma(): Sample from gamma distribution

sample_norm(): Sample from normal distribution

sample_vm(): Sample from von Mises distribution

simulate_track(): Generate track from simulated data

starize(): Natural parameters to working parameters (theta->theta.star)

starting_params_opt(): Generate starting parameters for a distribution

unstarize(): Working parameters to natural parameters (theta.star->theta)

viterbi_arp(): Global decoding for autoregressive HMM using Viterbi