iid2 {lavaSearch2} | R Documentation |
Influence Function With Small Sample Correction.
Description
Extract the influence function from a latent variable model.
It is similar to lava::iid
but with small sample correction.
Usage
iid2(object, ...)
## S3 method for class 'lvmfit'
iid2(
object,
robust = TRUE,
cluster = NULL,
as.lava = TRUE,
ssc = lava.options()$ssc,
...
)
## S3 method for class 'lvmfit2'
iid2(object, robust = TRUE, cluster = NULL, as.lava = TRUE, ...)
## S3 method for class 'lvmfit2'
iid(x, robust = TRUE, cluster = NULL, as.lava = TRUE, ...)
Arguments
object , x |
a |
... |
additional argument passed to |
robust |
[logical] if |
cluster |
[integer vector] the grouping variable relative to which the observations are iid. |
as.lava |
[logical] if |
ssc |
[character] method used to correct the small sample bias of the variance coefficients ( |
Details
When argument object is a lvmfit
object, the method first calls estimate2
and then extract the variance-covariance matrix.
Value
A matrix containing the 1st order influence function relative to each sample (in rows) and each model coefficient (in columns).
See Also
estimate2
to obtain lvmfit2
objects.
Examples
#### simulate data ####
n <- 5e1
p <- 3
X.name <- paste0("X",1:p)
link.lvm <- paste0("Y~",X.name)
formula.lvm <- as.formula(paste0("Y~",paste0(X.name,collapse="+")))
m <- lvm(formula.lvm)
distribution(m,~Id) <- Sequence.lvm(0)
set.seed(10)
d <- sim(m,n)
#### latent variable model ####
e.lvm <- estimate(lvm(formula.lvm),data=d)
iid.tempo <- iid2(e.lvm)