Nothing
# Implied model for precision. Requires appropriate model matrices:
implied_varcov <- function(model, all = FALSE){
if (model@cpp){
x <- formModelMatrices_cpp(model)
} else {
x <- formModelMatrices(model)
}
# Implied covariance structures:
if (model@cpp){
x <- impliedcovstructures_cpp(x,type = model@types$y, all = all)
} else {
x <- impliedcovstructures(x,type = model@types$y, all = all)
}
for (g in seq_along(x)){
# Check mu (if it is not there, this is because meanstructure = FALSE):
if (is.null(x[[g]]$mu)){
x[[g]]$mu <- as.matrix(model@sample@means[[g]])
}
# Check kappa
if (is.null(x[[g]]$kappa)){
x[[g]]$kappa <- solve_symmetric(x[[g]]$sigma, logdet = TRUE)
} else {
if (is.null(attr(x[[g]]$kappa, "logdet"))){
# ev <- eigen(x[[g]]$kappa, symmetric=TRUE, only.values=TRUE)$values
# Check pos-def:
# if(any(ev < sqrt(.Machine$double.eps)) || sum(ev) == 0) {
if (!sympd_cpp(x[[g]]$kappa)){
attr(x[[g]]$kappa, "logdet") <- log(.Machine$double.eps)
} else {
attr(x[[g]]$kappa, "logdet") <- determinant(x[[g]]$kappa, logarithm = TRUE)$modulus
}
}
}
}
x
}
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