Nothing
# Plotting function:
plot.lvglasso <- function(
x, # lvglasso x
plot = c("network","loadings","residcors","residpcors"), # "full" the full network, S" will plot the sparse network between items and "L" the latent loadings
ask,
rotation = promax, # A rotation function to be used.
...
){
if (missing(ask)) ask <- length(plot) > 1
parOrig <- par()
par(ask = ask)
obs <- x$observed
pcor <- x$pcor
Res <- list()
labs <- colnames(pcor)
if ("network" %in% plot){
Res$network <- qgraph(pcor, ..., title = "Estimated network", shape = ifelse(obs,"square", "circle"), layout = "spring")
}
if ("residpcors" %in% plot){
Res$residpcors <- qgraph(x$pcor[x$observed,x$observed], ..., title = "Estimated residual partial correlations", shape = "square", layout = "spring", repulsion = 0.9)
}
if ("residcors" %in% plot){
Res$residcors <- qgraph(cov2cor(x$theta), ..., title = "Estimated residual correlations", shape = "square", layout = "spring", repulsion = 0.9)
}
if ("loadings" %in% plot){
fCovs <- x$psi
load <- x$lambda
# Rotate:
rot <- rotation(load)
if (is.matrix(rot)){
load <- rot
rotmat <- matrix(1,1,1)
} else {
load <- rot$loadings
rotmat <- rot$rotmat
}
fCovs <- solve(rotmat) %*% fCovs %*% t(solve(rotmat))
rownames(load) <- colnames(x$wi)[obs]
Res$loadings <- qgraph.loadings(load, factorCors = fCovs, ..., title = "Estimated factor loadings", labels = colnames(x$wi)[obs], model = "reflective")
}
#
# if ("full" %in% plot){
# Res$S <- qgraph(pcor, ..., title = "Full structure", shape = ifelse(obs,"square", "circle"), layout = "spring")
# }
#
# if ("S" %in% plot){
# Res$S <- qgraph(pcor[obs,obs], ..., title = "Sparse structure", shape = "square", layout = "spring")
# }
#
# if ("L" %in% plot){
# fCors <- as.matrix(pcor[!obs,!obs])
# load <- as.matrix(pcor[obs,!obs])
#
# rownames(load) <- colnames(x$wi)[obs]
#
# Res$L <- qgraph.loadings(load, factorCors = fCors, arrows = FALSE,..., title = "Low-rank structure", labels = colnames(x$wi)[obs])
# }
#
invisible(Res)
}
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