initPHMM: Random Initialization for a Hidden Markov Model with...

In RcppHMM: Rcpp Hidden Markov Model

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

  n <- 2
  model <- initPHMM(n)
  print(model)

RcppHMM documentation built on May 2, 2019, 8:56 a.m.