con_gorica_est <- function(object, constraints = NULL, VCOV = NULL,
rhs = NULL, neq = 0L, mix_weights = "pmvnorm",
seed = NULL, control = list(), verbose = FALSE,
debug = FALSE, ...) {
if (is.null(VCOV)) {
stop("Restriktor ERROR: variance-covariance matrix VCOV must be provided.")
}
# check method to compute chi-square-bar weights
if (!(mix_weights %in% c("pmvnorm", "boot", "none"))) {
stop("Restriktor ERROR: ", sQuote(mix_weights), " method unknow. Choose from \"pmvnorm\", \"boot\", or \"none\"")
}
# timing
start.time0 <- start.time <- proc.time()[3]; timing <- list()
# store call
#mc <- match.call()
# rename for internal use
Amat <- constraints
bvec <- rhs
meq <- neq
b.unrestr <- object
b.unrestr[abs(b.unrestr) < ifelse(is.null(control$tol),
sqrt(.Machine$double.eps),
control$tol)] <- 0L
Sigma <- VCOV
# number of parameters
p <- length(b.unrestr)
# unrestricted log-likelihood
ll.unrestr <- dmvnorm(rep(0, p), sigma = Sigma, log = TRUE)
if (debug) {
print(list(loglik.unc = ll.unrestr))
}
timing$preparation <- (proc.time()[3] - start.time)
start.time <- proc.time()[3]
# deal with constraints
if (!is.null(constraints)) {
restr.OUT <- con_constraints(object,
VCOV = Sigma,
est = b.unrestr,
constraints = Amat,
bvec = bvec,
meq = meq,
mix_weights = mix_weights,
se = "none",
debug = debug)
# a list with useful information about the restriktions.}
CON <- restr.OUT$CON
# a parameter table with information about the observed variables in the object
# and the imposed restriktions.}
parTable <- restr.OUT$parTable
# constraints matrix
Amat <- restr.OUT$Amat
# rhs
bvec <- restr.OUT$bvec
# neq
meq <- restr.OUT$meq
} else if (is.null(constraints)) {
# no constraints specified - needed for GORIC to include unconstrained model
CON <- NULL
parTable <- NULL
Amat <- rbind(rep(0L, p))
bvec <- rep(0L, nrow(Amat))
meq <- 0L
}
# if only new parameters are defined and no constraints
if (length(Amat) == 0L) {
Amat <- rbind(rep(0L, p))
bvec <- rep(0L, nrow(Amat))
meq <- 0L
}
## create list for warning messages
messages <- list()
timing$constraints <- (proc.time()[3] - start.time)
start.time <- proc.time()[3]
if (ncol(Amat) != length(b.unrestr)) {
stop("Restriktor ERROR: length coefficients and the number of",
"\n columns constraints-matrix must be identical")
}
if (!(nrow(Amat) == length(bvec))) {
stop("nrow(Amat) != length(bvec)")
}
start.time <- proc.time()[3]
# check if the constraints are not in line with the data, else skip optimization
if (all(Amat %*% c(b.unrestr) - bvec >= 0 * bvec) & meq == 0) {
b.restr <- b.unrestr
OUT <- list(CON = CON,
#call = mc,
timing = timing,
parTable = parTable,
b.unrestr = b.unrestr,
b.restr = b.unrestr,
loglik = ll.unrestr,
Sigma = Sigma,
constraints = Amat,
rhs = bvec,
neq = meq,
wt.bar = NULL,
iact = 0L,
control = control)
} else {
# compute constrained estimates using quadprog
out.solver <- con_solver_gorica(est = b.unrestr,
VCOV = Sigma,
Amat = Amat,
bvec = bvec,
meq = meq)
b.restr <- out.solver$solution
names(b.restr) <- names(b.unrestr)
b.restr[abs(b.restr) < ifelse(is.null(control$tol), sqrt(.Machine$double.eps),
control$tol)] <- 0L
timing$optim <- (proc.time()[3] - start.time)
start.time <- proc.time()[3]
ll.restr <- dmvnorm(c(b.unrestr - b.restr), sigma = Sigma, log = TRUE)
OUT <- list(CON = CON,
#call = mc,
timing = timing,
parTable = parTable,
b.unrestr = b.unrestr,
b.restr = b.restr,
loglik = ll.restr,
Sigma = Sigma,
constraints = Amat,
rhs = bvec,
neq = meq,
wt.bar = NULL,
iact = out.solver$iact,
control = control)
}
Amat_meq_PT <- PT_Amat_meq(Amat, meq)
RREF <- Amat_meq_PT$RREF
PT_Amat <- Amat_meq_PT$PT_Amat
PT_meq <- Amat_meq_PT$PT_meq
OUT$PT_meq <- PT_meq
OUT$PT_Amat <- PT_Amat
if (mix_weights == "pmvnorm") {
if (RREF$rank < nrow(PT_Amat) && RREF$rank != 0L) {
messages$mix_weights_rank <- paste(
"Restriktor message: Since the constraint matrix is not full row-rank, the level probabilities",
"are calculated using mix_weights = \"boot\" (the default is mix_weights = \"pmvnorm\").",
"For more information see ?restriktor.\n"
)
mix_weights <- "boot"
}
}
## determine level probabilities
wt.bar <- calculate_weight_bar(Amat = PT_Amat, meq = PT_meq, VCOV = Sigma,
mix_weights = mix_weights, seed = seed,
control = control, verbose = verbose, ...)
attr(wt.bar, "method") <- mix_weights
OUT$wt.bar <- wt.bar
if (debug) {
print(list(mix_weights = wt.bar))
}
timing$mix_weights <- (proc.time()[3] - start.time)
OUT$messages <- messages
OUT$timing$total <- (proc.time()[3] - start.time0)
class(OUT) <- c("gorica_est")
OUT
}
con_gorica_est_lav <- function(x, standardized = FALSE, ...) {
## create empty list
out <- list()
## number of groups
#num_groups <- lavInspect(x, what = "ngroups")
## get parameter table
unstandardized_parTable <- parTable(x)
unstandardized_parTable <- unstandardized_parTable[unstandardized_parTable[, "plabel"] != "", ]
standardized_parTable <- standardizedSolution(x, ci = FALSE, zstat = FALSE, se = FALSE)$est.std
## combine unstandardized and standardized parameter estimates
parameter_table <- cbind(unstandardized_parTable, est.std = standardized_parTable)
## Only user-specified labels
parameter_table <- parameter_table[parameter_table$label != "" & parameter_table$free != 0L, ]
## remove any duplicate labels
parameter_table <- parameter_table[!duplicated(parameter_table$label), ]
## use (un)standardized parameter estimates
out$estimate <-
if (standardized) {
parameter_table$est.std
} else {
parameter_table$est
}
names(out$estimate) <- parameter_table$label
## extract (un)standardized VCOV
out$VCOV <-
if (standardized) {
lavInspect(x, "vcov.std.all")
} else {
lavInspect(x, "vcov")
}
## remove not used columns of VCOV
out$VCOV <- out$VCOV[parameter_table$label, parameter_table$label, drop = FALSE]
out
}
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