pn2pw: pn2pw

In countHMM: Penalized Estimation of Flexible Hidden Markov Models for Time Series of Counts

Description

Transforming natural parameters to working parameters. Not intended to be run by the user (internal function, called by the functions nLogLike and fitMod).

Usage

pn2pw(N,probs,gamma,delta,stationary)

Arguments

N	Number of states.
probs	Matrix with N columns which contains the state-dependent probabilities for each count.
gamma	Transition probability matrix of the Markov chain underlying the observed counts with N rows and N columns.
delta	Initial distribution vector of length N of the Markov chain underlying the observed counts. If NULL, then the stationary distribution is returned.
stationary	Logical, determines whether the initial distribution of the Markov chain underlying the observed counts is the stationary distribution.

Value

A vector of working parameters.

Examples

# transforming natural parameters to working paramters
pn2pw(N=2,probs=cbind(dpois(x=0:41,lambda=14),dpois(x=0:41,lambda=26)),
gamma=matrix(c(0.95,0.05,0.05,0.95),ncol=2),delta=NULL,stationary=TRUE)

countHMM documentation built on May 2, 2019, 1:06 p.m.