rmixmvnorm {hhsmm} | R Documentation |
Random data generation from the mixture of multivariate normals for hhsmm model
Description
Generates a vector of observations from mixture multivariate normal distribution in a specified state and using the parameters of a specified model
Usage
rmixmvnorm(j, model)
Arguments
j |
a specified state |
model |
a |
Value
a random vector of observations from mixture of multivariate normal distributions
Author(s)
Morteza Amini, morteza.amini@ut.ac.ir, Afarin Bayat, aftbayat@gmail.com
Examples
J <- 3
initial <- c(1, 0, 0)
semi <- c(FALSE, TRUE, FALSE)
P <- matrix(c(0.8, 0.1, 0.1, 0.5, 0, 0.5, 0.1, 0.2, 0.7), nrow = J,
byrow = TRUE)
par <- list(mu = list(list(7, 8), list(10, 9, 11), list(12, 14)),
sigma = list(list(3.8, 4.9), list(4.3, 4.2, 5.4), list(4.5, 6.1)),
mix.p = list(c(0.3, 0.7), c(0.2, 0.3, 0.5), c(0.5, 0.5)))
sojourn <- list(shape = c(0, 3, 0), scale = c(0, 10, 0), type = "gamma")
model <- hhsmmspec(init = initial, transition = P, parms.emis = par,
dens.emis = dmixmvnorm, sojourn = sojourn, semi = semi)
x = rmixmvnorm(1, model)
[Package hhsmm version 0.4.0 Index]