Nothing
## utility functions
coef.restriktor <- function(object, ...) {
b.def <- c()
b.restr <- object$b.restr
if (any(object$parTable$op == ":=")) {
b.def <- object$CON$def.function(object$b.restr)
}
if (inherits(object, "conMLM")) {
OUT <- rbind(b.restr, b.def)
} else {
OUT <- c(b.restr, b.def)
}
return(OUT)
}
coef.con_goric <- function(object, ...) {
return(object$ormle$b.restr)
}
coef.gorica_est <- function(object, ...) {
return(object$b.restr)
}
logLik.restriktor <- function(object, ...) {
return(object$loglik)
}
model.matrix.restriktor <- function(object, ...) {
return(model.matrix(object$model.org))
}
tukeyChi <- function(x, c = 4.685061, deriv = 0, ...) {
u <- x / c
out <- abs(x) > c
if (deriv == 0) { # rho function
r <- 1 - (1 - u^2)^3
r[out] <- 1
} else if (deriv == 1) { # rho' = psi function
r <- 6 * x * (1 - u^2)^2 / c^2
r[out] <- 0
} else if (deriv == 2) { # rho''
r <- 6 * (1 - u^2) * (1 - 5 * u^2) / c^2
r[out] <- 0
} else {
stop("deriv must be in {0,1,2}")
}
return(r)
}
# code taken from robustbase package.
# addapted by LV (3-12-2017).
robWeights <- function(w, eps = 0.1/length(w), eps1 = 0.001, ...) {
stopifnot(is.numeric(w))
cat("Robustness weights:", "\n")
cat0 <- function(...) cat("", ...)
n <- length(w)
if (n <= 10)
print(w, digits = 5, ...)
else {
n1 <- sum(w1 <- abs(w - 1) < eps1)
n0 <- sum(w0 <- abs(w) < eps)
if (any(w0 & w1))
warning("weights should not be both close to 0 and close to 1!\n",
"You should use different 'eps' and/or 'eps1'")
if (n0 > 0 || n1 > 0) {
if (n0 > 0) {
formE <- function(e) formatC(e, digits = max(2,
5 - 3), width = 1)
i0 <- which(w0)
maxw <- max(w[w0])
c3 <- paste0("with |weight| ", if (maxw == 0)
"= 0"
else paste("<=", formE(maxw)), " ( < ", formE(eps),
");")
cat0(if (n0 > 1) {
cc <- sprintf("%d observations c(%s)", n0,
strwrap(paste(i0, collapse = ",")))
c2 <- " are outliers"
paste0(cc, if (nchar(cc) + nchar(c2) + nchar(c3) >
getOption("width"))
"\n\t", c2)
}
else sprintf("observation %d is an outlier",
i0), c3, "\n")
}
if (n1 > 0)
cat0(ngettext(n1, "one weight is", sprintf("%s%d weights are",
if (n1 == n)
"All "
else "", n1)), "~= 1.")
n.rem <- n - n0 - n1
if (n.rem <= 0) {
if (n1 > 0)
cat("\n")
return(invisible())
}
}
}
}
# function taken from 'bain' package
expand_compound_constraints <- function(hyp) {
equality_operators <- gregexpr("[=<>]", hyp)[[1]]
if(length(equality_operators) > 1){
string_positions <- c(0, equality_operators, nchar(hyp)+1)
return(sapply(1:(length(string_positions)-2), function(pos) {
substring(hyp, (string_positions[pos]+1), (string_positions[pos+2]-1))
}))
} else {
return(hyp)
}
}
# function taken from 'bain' package
expand_parentheses <- function(hyp) {
parenth_locations <- gregexpr("[\\(\\)]", hyp)[[1]]
if (!parenth_locations[1] == -1 & !grepl("abs\\(.*\\)", hyp) ) {
if (length(parenth_locations) %% 2 > 0) stop("Not all opening parentheses are matched by a closing parenthesis, or vice versa.")
expanded_contents <- strsplit(substring(hyp, (parenth_locations[1]+1), (parenth_locations[2]-1)), ",")[[1]]
if (length(parenth_locations) == 2){
return(paste0(substring(hyp, 1, (parenth_locations[1]-1)), expanded_contents, substring(hyp, (parenth_locations[2]+1), nchar(hyp))))
} else {
return(apply(
expand.grid(expanded_contents, expand_parentheses(substring(hyp, (parenth_locations[2]+1), nchar(hyp)))),
1, paste, collapse = ""))
}
} else {
return(hyp)
}
}
format_numeric <- function(x, digits = 3) {
if (abs(x) <= 1e-8) {
format(0, nsmall = digits)
} else if (abs(x) >= 1e3 || abs(x) <= 1e-3) {
format(x, scientific = TRUE, digits = digits)
} else {
format(round(x, digits), nsmall = digits)
}
}
# compute_weights_ratioWeights <- function(x) {
# IC <- 2*x
# minIC <- min(IC)
# weights <- exp(-0.5 * (IC - minIC)) / sum(exp(-0.5 * (IC - minIC)))
# ratio_weights <- weights %*% t(1/weights)
#
# out <- list(weights = weights, ratio_weights = ratio_weights)
#
# return(out)
# }
#
# remove_linear_dependent_rows_matrix <- function(Amat, bvec) {
# ## remove any linear dependent rows from the constraint matrix. Amat must be of full row rank.
# # remove any zero vectors
# allZero.idx <- rowSums(abs(Amat)) == 0
# Amat <- Amat[!allZero.idx, , drop = FALSE]
# bvec <- bvec[!allZero.idx]
# # what is the rank of Amat
# rank <- qr(Amat)$rank
# # decompose Amat using svd
# s <- svd(Amat)
# # continue untill Amat is of full-row rank
# while (rank != length(s$d)) {
# # check which singular values are zero
# zero.idx <- which(zapsmall(s$d) <= 1e-16)
# # remove linear dependent rows and reconstruct the constraint matrix
# Amat <- s$u[-zero.idx, ] %*% diag(s$d) %*% t(s$v)
# # zapping small ones to zero
# Amat <- zapsmall(Amat)
# bvec <- bvec[-zero.idx]
# s <- svd(Amat)
# }
#
# OUT <- list(Amat, bvec)
#
# OUT
# }
#
#rankifremoved <- sapply(1:ncol(Amat), function (x) qr(Amat[-x, ])$rank)
#which(rankifremoved == max(rankifremoved))
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