dmixmvnorm: pdf of the mixture of multivariate normals for hhsmm

Description Usage Arguments Value Author(s) Examples

View source: R/dmvnorm-mix-hhsmm.R

Description

The probability density function of a mixture multivariate normal for a specified observation vector, a specified state and a specified model's parameters

Usage

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dmixmvnorm(x, j, model)

Arguments

x

an observation vector or matrix

j

a specified state between 1 to nstate

model

a hhsmmspec model

Value

the probability density function value

Author(s)

Morteza Amini, morteza.amini@ut.ac.ir, Afarin Bayat, aftbayat@gmail.com

Examples

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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)
p = dmixmvnorm(train$x,1,model)

hhsmm documentation built on Jan. 10, 2022, 9:07 a.m.

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