Learn R Programming

LaMa (version 1.0.0)

tpm: Build the transition probability matrix from unconstraint parameter vector

Description

This function builds the transition probability matrix from an unconstraint parameter vector. For each row of the matrix, the inverse multinomial logistic link is applied.

Usage

tpm(param, byrow = FALSE)

Value

Transition probability matrix of dimension c(N,N)

Arguments

param

Unconstraint parameter vector of length N*(N-1) where N is the number of states of the Markov chain

byrow

Logical that indicates if the transition probability matrix should be filled by row. Defaults to FALSE, but should be set to TRUE if one wants to work with a matrix of beta parameters returned by popular HMM packages like moveHMM, momentuHMM, or hmmTMB.

Examples

Run this code
# 2 states: 2 free off-diagonal elements
param1 = rep(-1, 2)
Gamma1 = tpm(param1)

# 3 states: 6 free off-diagonal elements
param2 = rep(-2, 6)
Gamma2 = tpm(param2)

Run the code above in your browser using DataLab