make_model  R Documentation 
Provides a hhsmmspec model by using the parameters
obtained by initial_estimate
for the emission distribution
characterized by mstep and dens.emission
make_model(
par,
mstep = mixmvnorm_mstep,
dens.emission = dmixmvnorm,
semi = NULL,
M,
sojourn
)
par 
the parameters obtained by 
mstep 
the mstep function of the EM algorithm with an style simillar to that of 
dens.emission 
the density of the emission distribution with an style simillar to that of 
semi 
logical and of one of the following forms:

M 
maximum number of waiting times in each state 
sojourn 
the sojourn time distribution which is one of the following cases:

a hhsmmspec
model containing the following items:
init
initial probabilities of states
transition
transition matrix
parms.emission
parameters of the mixture normal emission (mu
, sigma
, mix.p
)
sojourn
list of sojourn distribution parameters and its type
dens.emission
the emission probability density function
mstep
the M step function of the EM algorithm
semi
a logical vector of length nstate with the TRUE associated states are considered as semiMarkovian
Morteza Amini, morteza.amini@ut.ac.ir, Afarin Bayat, aftbayat@gmail.com
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)
clus = initial_cluster(train, nstate = 3, nmix = c(2, 2, 2), ltr = FALSE,
final.absorb = FALSE, verbose = TRUE)
par = initial_estimate(clus, verbose = TRUE)
model = make_model(par, semi = NULL, M = max(train$N), sojourn = "gamma")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.