rmultinomial.hhsmm: Random data generation from the multinomial emission...

In hhsmm: Hidden Hybrid Markov/Semi-Markov Model Fitting

Random data generation from the multinomial emission distribution for hhsmm model

Description

Generates a vector of observations from multinomial emission distribution in a specified state and using the parameters of a specified model

Usage

rmultinomial.hhsmm(j, model)

Arguments

j	a specified state
model	a hhsmmspec model

Value

a random vector of observations from multinomial emission distribution

Author(s)

Morteza Amini, [e-mail]

Examples

J <- 2
initial <- c(1, 0)
semi <- rep(TRUE, 2)
P <- matrix(c(0, 1, 1, 0), 
nrow = J, byrow = TRUE)
par <- list(prob = list(c(0.6,  0.2, 0.2),
                           c(0.2, 0.6,  0.2)))
sojourn <- list(shape = c(1, 3), scale = c(2, 10), type = "gamma")
model <- hhsmmspec(init = initial, transition = P, parms.emis = par,
dens.emis = dmultinomial.hhsmm, remission = rmultinomial.hhsmm,
 mstep = mstep.multinomial,sojourn = sojourn, semi = semi)
train <- simulate(model, nsim = c(20, 30, 42, 50), seed = 1234, 
remission = rmultinomial.hhsmm)
plot(train)

hhsmm documentation built on Sept. 11, 2024, 7:34 p.m.