drobust: pdf of the mixture of the robust emission proposed by Qin et...

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

pdf of the mixture of the robust emission proposed by Qin et al. (2024)

Description

The probability density function of the robust emission proposed by Qin et al. (2024) for a specified observation vector, a specified state and a specified model's parameters

Usage

drobust(x, j, model, control = list(k = 1.345))

Arguments

x	an observation vector or matrix
j	a specified state between 1 to nstate
model	a hhsmmspec model
control	a list containing the control parameter k with the default value equal to 1.345

Value

the probability density function value

Author(s)

Morteza Amini, [e-mail]

References

Qin, S., Tan, Z., and Wu, Y. (2024). On robust estimation of hidden semi-Markov regime-switching models. Annals of Operations Research, 1-33.

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)
train <- simulate(model, nsim = c(10, 8, 8, 18), seed = 1234, 
remission = rmixmvnorm)
mu = list(0,1)
sigma = list(1,2)
robustmodel = list(parms.emission = list(mu = mu,sigma = sigma))
p = drobust(train$x, 1, robustmodel)

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