Composite Likelihood for probit latent variable models
Estimate parameters in a probit latent variable model via a composite likelihood decomposition.
complik(
x,
data,
k = 2,
type = c("all", "nearest"),
pairlist,
messages = 0,
estimator = "normal",
quick = FALSE,
...
)x |
|
data |
data.frame |
k |
Size of composite groups |
type |
Determines number of groups. With |
pairlist |
A list of indices specifying the composite groups. Optional
argument which overrides |
messages |
Control amount of messages printed |
estimator |
Model (pseudo-likelihood) to use for the pairs/groups |
quick |
If TRUE the parameter estimates are calculated but all additional information such as standard errors are skipped |
... |
Additional arguments parsed on to lower-level functions |
An object of class estimate.complik inheriting methods from lvm
Klaus K. Holst
estimate
m <- lvm(c(y1,y2,y3)~b*x+1*u[0],latent=~u)
ordinal(m,K=2) <- ~y1+y2+y3
d <- sim(m,50,seed=1)
if (requireNamespace("mets", quietly=TRUE)) {
e1 <- complik(m,d,control=list(trace=1),type="all")
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