plot.hmm_mcmc_normal {oHMMed}

Plot Diagnostics for hmm_mcmc_normal Objects

Description

This function creates a variety of diagnostic plots that can be useful when conducting Markov Chain Monte Carlo (MCMC) simulation of a normal hidden Markov model (HMM). These plots will help to assess convergence, fit, and performance of the MCMC simulation

Usage

## S3 method for class 'hmm_mcmc_normal'
plot(
  x,
  simulation = FALSE,
  true_means = NULL,
  true_sd = NULL,
  true_mat_T = NULL,
  true_states = NULL,
  show_titles = TRUE,
  ...
)

Arguments

x

(hmm_mcmc_normal) HMM MCMC normal object

simulation

(logical) optional parameter; default is simulation=FALSE, so the input data was empirical. If the input data was simulated, it must be set simulation=TRUE.

true_means

(numeric) optional parameter; true means. To be used if simulation=TRUE

true_sd

(numeric) optional parameter; true standard deviation. To be used if simulation=TRUE

true_mat_T

(matrix) optional parameter; true transition matrix. To be used if simulation=TRUE

true_states

(integer) optional parameter; true states. To be used if simulation=TRUE

show_titles

(logical) optional parameter; if TRUE then titles are shown for all graphs. By default, TRUE

...

not used

Value

Several diagnostic plots that can be used to evaluate the MCMC simulation of the normal HMM

Examples

plot(example_hmm_mcmc_normal)