View source: R/sCorrect-skeleton.R
skeleton | R Documentation |
Pre-compute quantities that are necessary to compute the score of a lvm model.
skeleton(object, X, endogenous, latent, n.cluster, index.Omega)
skeletonDtheta(
object,
X,
endogenous,
latent,
missing.pattern,
unique.pattern,
name.pattern,
n.cluster,
index.Omega
)
skeletonDtheta2(object)
object |
a |
X |
[matrix] design matrix containing the covariates for each endogeneous and latent variable. |
endogenous |
[character vector] the name of the endogeneous variables. |
latent |
[character vector] the name of the latent variables. |
When the user specifies names for the coefficients (e.g. Y1[mu:sigma]) or uses constraints (Y1~beta*X1), as.lava=FALSE
will use the names specified by the user (e.g. mu, sigma, beta)
while as.lava=TRUE
will use the name of the first link defining the coefficient.
## Not run:
skeleton <- lavaSearch2::skeleton
skeleton.lvm <- lavaSearch2::skeleton.lvm
skeleton.lvmfit <- lavaSearch2::skeleton.lvmfit
## without constrain
m <- lvm(Y1~X1+X2+eta,Y2~X3+eta,Y3~eta)
latent(m) <- ~eta
e <- estimate(m, lava::sim(m,1e2))
M.data <- as.matrix(model.frame(e))
skeleton(e$model, as.lava = TRUE,
name.endogenous = endogenous(e), n.endogenous = 3,
name.latent = latent(e),
update.value = FALSE)
skeleton(e, data = M.data, p = pars(e), as.lava = TRUE,
name.endogenous = endogenous(e), n.endogenous = 3,
name.latent = latent(e),
update.value = TRUE)
## with constrains
m <- lvm(Y[mu:sigma] ~ beta*X1+X2)
e <- estimate(m, lava::sim(m,1e2))
M.data <- as.matrix(model.frame(e))
skeleton(e$model, as.lava = TRUE,
name.endogenous = "Y", n.endogenous = 1,
name.latent = NULL,
update.value = FALSE)$skeleton
skeleton(e, data = M.data, p = pars(e), as.lava = FALSE,
name.endogenous = "Y", n.endogenous = 1,
name.latent = NULL,
update.value = FALSE)$skeleton
## End(Not run)
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