Nothing
set.seed(1234)
# ----- Univariate ----- #
# Define DGP
mdl_hmm <- list(n = 1000,
q = 1,
mu = as.matrix(c(5,-2)),
sigma = list(as.matrix(5.0),
as.matrix(7.0)),
k = 2,
P = rbind(c(0.90, 0.10),
c(0.10, 0.90)))
# Simulate process using simuHMM() function
y_hmm_simu <- simuHMM(mdl_hmm)
# Set options for model estimation
control <- list(msmu = TRUE,
msvar = TRUE,
method = "EM",
use_diff_init = 1)
# Estimate model
y_hmm_mdl <- HMmdl(y_hmm_simu$y, k = 2, control = control)
summary(y_hmm_mdl)
# ----- Multivariate normal process ----- #
# Define DGP
mdl_hmm <- list(n = 500,
q = 2,
mu = rbind(c(5, -2),
c(10, 2)),
sigma = list(rbind(c(5.0, 1.5),
c(1.5, 1.0)),
rbind(c(7.0, 3.0),
c(3.0, 2.0))),
k = 2,
P = rbind(c(0.90, 0.10),
c(0.10, 0.90)))
# Simulate process using simuHMM() function
y_hmm_simu <- simuHMM(mdl_hmm)
# Set options for model estimation
control <- list(msmu = TRUE,
msvar = TRUE,
method = "EM",
use_diff_init = 1)
# Estimate model
\donttest{
y_hmm_mdl <- HMmdl(y_hmm_simu$y, k = 2, control = control)
summary(y_hmm_mdl)
}
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