RcppHMM (version 1.2.2)

initPHMM: Random Initialization for a Hidden Markov Model with emissions modeled as discrete variables

Description

Function used to generate a hidden Markov model with discrete observations and random parameters. This model is used when the observed data are counts that can be modelled with a mixture of Poissons. The code for the methods with categorical values or continuous data can be viewed in "initHMM" and "initGHMM", respectively.

Usage

initPHMM(n)

Arguments

n

the number of hidden states to use.

Value

A "list" that contains all the required values to specify the model.

Model

it specifies that the observed values are to be modeled as a Poisson mixture model.

StateNames

the set of hidden state names.

A

the transition probabilities matrix.

B

a vector with the lambda parameter for each Poisson distribution.

Pi

the initial probability vector.

References

Cited references are listed on the RcppHMM manual page.

Examples

# NOT RUN {
  n <- 2
  model <- initPHMM(n)
  print(model)
# }