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

In RcppHMM: Rcpp Hidden Markov Model

Description

Function used to generate a hidden Markov model with categorical variables and random parameters. The code for the methods with continuous values or discrete data can be viewed in "initGHMM" and "initPHMM", respectively.

Usage

initHMM(n, m)

Arguments

n	the number of hidden states to use.
m	the number of possible categories (labels) generated by the hidden states.

Value

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

Model	it specifies that the observed values are to be modeled as a multinomial distribution.
StateNames	the set of hidden state names.
ObservationNames	the set of possible observed values.
A	the transition probabilities matrix.
B	the emission probabilities matrix.
Pi	the initial probability vector.

References

Cited references are listed on the RcppHMM manual page.

Examples

n <- 2
m <- 2
model <- initHMM(n,m)
print(model)

Example output

Attaching package: 'RcppHMM'

The following object is masked from 'package:stats':

    setNames

$Model
[1] "HMM"

$StateNames
[1] "x1" "x2"

$ObservationNames
[1] "y1" "y2"

$A
          [,1]      [,2]
[1,] 0.4533246 0.5466754
[2,] 0.8037148 0.1962852

$B
          [,1]      [,2]
[1,] 0.1510980 0.8489020
[2,] 0.4375402 0.5624598

$Pi
[1] 0.8153173 0.1846827

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