Nothing
test_that("support_npmsm", {
skip_if(TRUE)
tmat <- mstate::transMat(x = list( c(2, 3), c(3), c() ))
set.seed(1)
#Absorbing states 4 and 6
qmatrix <- rbind(
c(-0.15, 0.1, 0.05),
c(0, -0.1, 0.1),
c(0, 0, 0)
)
n <- 10
gd <- NULL
for (i in 1:n) {
smsm <- msm::sim.msm(qmatrix, 14)
# inspection times uniformly on 2 year intervals until 14 years
itimes <- seq(2, 24, by=3) + runif(8, 0, 2)
gdi <- data.frame(id=i, state=evalstep(time=smsm$times, stepf=smsm$states,
newtime=c(0,itimes)), time=c(0,itimes))
# throw away superfluous duplicate state 3 (absorbing)
gdi <- gdi[!(gdi$state==3 & duplicated(gdi$state)),]
gd <- rbind(gd, gdi)
}
gd_eid <- NULL
for(j in unique(gd$id)){
tempdat <- subset(gd, id == j)
tempstates <- unique(tempdat$state)
#If we observe 3 unique states, 1->2->3 must have happened
if(length(tempstates) == 3){
tempdat$state[which(tempdat$state == 3)] <- 4
}
gd_eid <- rbind(gd_eid, tempdat)
}
tmat_eid <- mstate::transMat(x = list( c(2, 3), c(4), c(), c() ))
out_msm_eid <- npmsm(gd_eid, tmat_eid, maxit = 200, tol = 1e-8, exact = c(3, 4))
})
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