Nothing
# automatically select computation.method:
# L-moments: recursive
# TL-moments: recurrence
# NI-TL-moments: direct
select_computation <- function(leftrim, rightrim) {
stopifnot(is.numeric(leftrim), is.numeric(rightrim))
if (isTRUE(all.equal(leftrim, 0L)) & isTRUE(all.equal(rightrim, 0L))) {
return("recursive")
} else if (are.integer.like(leftrim, rightrim)) {
return("recurrence")
} else {
return("direct")
}
}
# calculate pseudo observations
pseudo <- function(x, k) {
as.matrix(pseudo_C(sort(stats::na.omit(x)), k)[rank(x, na.last = "keep"), ])
}
# Functions for general error catching
are.integer.like <- function(...) {
all(vapply(list(...), function(a) isTRUE(all.equal(a, as.integer(a))), logical(1)))
}
are.numeric <- function(...) {
all(vapply(list(...), function(a) is.numeric(a), logical(1)))
}
`%in.equal%` <- function(a, b) {
r <- vapply(a, function(.a) vapply(b, function(.b) { isTRUE(all.equal(.a, .b)) }, logical(1)), logical(length(b)))
if (is.null(dim(r))) {
r
} else {
apply(r, 2, any)
}
}
# infix for intervals
`%-+%` <- function(a, b) { cbind(a - b, a + b) }
# @description Calculates TL-Moments for every distribution in distr for the specified trim.
# Used by plot.TLMoments
# @return data.frame
# @examples
# getTLMomsByDistr(c("gev", "gpd", "gum", "norm", "ln3", "pe3", "glo"), c(2, 1))
getTLMomsByDistr <- function(distr, trim) {
# "Lines" & "Points"
.lines <- function(distr, shapes, trim) {
if (distr %in% c("gev", "gpd", "ln3")) {
sapply(shapes, function(shape) {
r <- tryCatch(
calcTLMom(4, trim[1], trim[2], qfunc = getQ.character(distr, loc = 0, scale = 1, shape = shape)),
error = function(e) rep(NA, 4)
)
setNames(r, paste0("L", 1:4))
})
} else if (distr == "pe3") {
sapply(shapes, function(shape) {
r <- tryCatch(
calcTLMom(4, trim[1], trim[2], qfunc = function(p) lmomco::quape3(p, lmomco::vec2par(c(0, 1, shape), "pe3"))),
error = function(e) rep(NA, 4)
)
setNames(r, paste0("L", 1:4))
})
} else if (distr == "glo") {
sapply(shapes, function(shape) {
r <- tryCatch(
calcTLMom(4, trim[1], trim[2], qfunc = function(p) lmomco::quaglo(p, lmomco::vec2par(c(0, 1, shape), "glo"))),
error = function(e) rep(NA, 4)
)
setNames(r, paste0("L", 1:4))
})
} else {
stop("Unsupported distribution. ")
}
}
.points <- function(distr, trim) tryCatch(calcTLMom(4, trim[1], trim[2], qfunc = getQ.character(distr)), error = function(e) rep(NA, 4))
if ("gum" %in% distr) {
gum <- data.frame(
distr = "gum",
leftrim = trim[1],
rightrim = trim[2],
shape = NA,
data.frame(t(setNames(.points("gum", trim), paste0("L", 1:4))))
)
} else gum <- NULL
if ("exp" %in% distr) {
exp <- data.frame(
distr = "exp",
leftrim = trim[1],
rightrim = trim[2],
shape = NA,
data.frame(t(setNames(.points("exp", trim), paste0("L", 1:4))))
)
} else exp <- NULL
if ("norm" %in% distr) {
norm <- data.frame(
distr = "norm",
leftrim = trim[1],
rightrim = trim[2],
shape = NA,
data.frame(t(setNames(.points("norm", trim), paste0("L", 1:4))))
)
} else norm <- NULL
if ("gev" %in% distr) {
shapes <- c(seq(-20, -5), seq(-5+.01, 5-.01, .01))
gev <- data.frame(
distr = "gev",
leftrim = trim[1],
rightrim = trim[2],
cbind(
shape = shapes,
t(.lines("gev", shapes, trim))
)
)
} else gev <- NULL
if ("gpd" %in% distr) {
shapes <- c(seq(-100, -5), seq(-5+.01, 5-.01, .01))
gpd <- data.frame(
distr = "gpd",
leftrim = trim[1],
rightrim = trim[2],
cbind(
shape = shapes,
t(.lines("gpd", shapes, trim))
)
)
} else gpd <- NULL
if ("ln3" %in% distr) {
shapes <- c(seq(.001, .01, length.out = 10), seq(.01, 5, .01))
ln3 <- data.frame(
distr = "ln3",
leftrim = trim[1],
rightrim = trim[2],
cbind(
shape = shapes,
t(.lines("ln3", shapes, trim))
)
)
} else ln3 <- NULL
if ("pe3" %in% distr) {
shapes <- seq(-10, 10, .1)
pe3 <- data.frame(
distr = "pe3",
leftrim = trim[1],
rightrim = trim[2],
cbind(
shape = shapes,
t(.lines("pe3", shapes, trim))
)
)
} else pe3 <- NULL
if ("glo" %in% distr) {
shapes <- c(seq(-1, -.9, .001), seq(-.9, .9, .01), seq(.9, 1, .001))#seq(-.99, .99, .01)
glo <- data.frame(
distr = "glo",
leftrim = trim[1],
rightrim = trim[2],
cbind(
shape = shapes,
t(.lines("glo", shapes, trim))
)
)
} else glo <- NULL
dat <- rbind(gum, exp, norm, gev, gpd, ln3, pe3, glo)
dat$T3 <- dat$L3 / dat$L2
dat$T4 <- dat$L4 / dat$L2
dat <- dat[!(is.na(dat$T3) | is.na(dat$T4)), ]
dat
}
# @description calculates the first maxr TL-moments of order s, t given a quantile function qfunc
# @examples
# calcTLMom(4, 0, 2, function(u) evd::qgumbel(u, loc = 0, scale = 1))
# lmomco::theoTLmoms(lmomco::vec2par(c(0, 1), type = "gum"), nmom = 4, leftrim = 0, rightrim = 2)$lambdas
#
# calcTLMom(4, 2, 1, function(u) evd::qgev(u, loc = 0, scale = 1, shape = .2))
# lmomco::theoTLmoms(lmomco::vec2par(c(0, 1, -.2), type = "gev"), nmom = 4, leftrim = 2, rightrim = 1)$lambdas
#
# microbenchmark::microbenchmark(
# calcTLMom(4, 2, 1, function(u) evd::qgev(u, loc = 0, scale = 1, shape = .2)),
# lmomco::theoTLmoms(lmomco::vec2par(c(0, 1, -.2), type = "gev"), nmom = 4, leftrim = 2, rightrim = 1)$lambdas
# )
calcTLMom <- function(maxr, s, t, qfunc, ...) {
#if (!are.integer.like(maxr, s, t)) stop("s, t, and maxr have to be integer-like. ")
if (s < 0 | t < 0 | maxr < 1) stop("s and t have to be >= 0, maxr has to be >= 1. ")
if (!is.function(qfunc)) stop("qfunc has to be a function. ")
vapply(1L:maxr, function(r) {
sum(vapply(0:(r-1), function(j) {
tryCatch(
i <- stats::integrate(f <- function(u) u^(s+j) * (1-u)^(t+r-j-1) * qfunc(u, ...), lower = 0, upper = 1),
error = function(e) stop(e)
)
if (i$message != "OK") stop("Error occurred while integrating. ")
(-1)^(r-j-1) * factorial(r-1)*factorial(r+s+t) /r /factorial(j) /factorial(r+t-j-1) /factorial(r-j-1) /factorial(s+j) * i$value
}, numeric(1)))
}, numeric(1))
}
# @param args vector of characters giving the argument names to check
# @param distr character
checkParameterNames <- function(args, distr) {
stopifnot(length(distr) == 1)
stopifnot(is.character(args))
if (grepl("::", x = distr)) { # if pkg::func
f <- sub("^([a-zA-Z0-9]*)::([a-zA-Z0-9]*)$", "\\1::q\\2", x = distr)
q <- eval(parse(text = paste0("match.fun(", f,")")))
} else { # falls nur func
q <- eval(parse(text = paste0("match.fun(q", distr, ")")))
}
.args <- names(formals(q))[sapply(formals(q), is.numeric)]
args <- .args[pmatch(args, .args, nomatch = NA)]
if (any(is.na(args))) stop("Names do not match distribution arguments or are ambiguous. ")
args
}
# @description extracts the quantile function of a parameters-object or a character string (like evd::gev)
# @examples
# getQ(as.parameters(loc = 9, scale = 5, shape = .3, distr = "evd::gev"))
# getQ("evd::gev", loc = 10, scale = 4, shape = .2)
getQ <- function(x, ...) {
if (!inherits(x, c("parameters", "character")))
stop("x must be of class parameters or character vector")
UseMethod("getQ")
}
getQ.character <- function(x, ...) {
distr <- x
args <- list(...)
if (grepl("::", x = distr)) { # if pkg::func
f <- sub("^([a-zA-Z0-9]*)::([a-zA-Z0-9]*)$", "\\1::q\\2", x = distr)
q <- eval(parse(text = paste0("match.fun(", f,")")))
} else { # falls nur func
q <- eval(parse(text = paste0("match.fun(q", distr, ")")))
}
if (!is.function(q)) stop(paste0("Found no q-function for ", distr))
if (any(!(names(args) %in% names(formals(q))))) stop("Wrong arguments given.")
formals(q)[names(args)] <- args
q
}
getQ.parameters <- function(x) {
if (!inherits(x, "numeric")) stop("By now only for parameters, numeric!")
distr <- attr(x, "distribution")
args <- as.list(x)
do.call(getQ.character, c(x = distr, args))
}
correctNames <- function(x, forbidden_pattern, preceding) {
if (inherits(x, "data.frame")) {
forbids <- grepl(forbidden_pattern, names(x))
if (any(forbids)) {
forbidden_names <- names(x)[forbids]
new_names <- paste0(preceding, forbidden_names)
names(x)[forbids] <- new_names
warning("Renamed variables due to invalid names. ")
}
} else if (inherits(x, "formula")) {
forbids <- grepl(forbidden_pattern, all.vars(x))
if (any(forbids)) {
forbidden_names <- all.vars(x)[forbids]
strformula <- deparse(x)
for (i in seq_along(forbidden_names)) {
strformula <- sub(forbidden_names[i], paste0(preceding, forbidden_names[i]), strformula)
}
x <- as.formula(strformula)
warning("Renamed variables due to invalid names. ")
}
}
x
}
calcRatios <- function(lambdas) {
if (length(lambdas) > 2L) {
out <- c(NA, lambdas[2]/lambdas[1], lambdas[3:length(lambdas)]/lambdas[2])
} else if (length(lambdas) == 2L) {
out <- c(NA, lambdas[2]/lambdas[1])
} else {
out <- NA
}
setNames(out, paste0("T", seq_along(out)))
}
calcLambdas <- function(ratios, L1) {
if (is.na(L1)) {
L1 <- 1
warning("L1 is assumed to be 1. ")
}
if (length(ratios) > 1L) {
out <- c(L1, ratios[1]*L1, ratios[2:length(ratios)]*(ratios[1]*L1))
} else if (length(ratios) == 1L) {
out <- c(L1, ratios[1]*L1)
} else {
out <- L1
}
setNames(out, paste0("L", seq_along(out)))
}
getFormulaSides <- function(formula, names = NULL) {
lhs <- all.vars(update(formula, .~0))
all <- all.vars(formula)
rhs <- all[!(all %in% lhs)]
if (!is.null(names)) {
if (length(lhs) == 1 && lhs == ".") {
lhs <- names[!(names %in% rhs)]
}
if (length(rhs) == 1 && rhs == ".") {
rhs <- names[!(names %in% lhs)]
}
if ("." %in% all) all <- names
#if (!all(lhs %in% names)) stop("Formula error")
#if (!all(rhs %in% names)) stop("Formula error")
}
list(lhs = lhs, rhs = rhs, all = all,
new.formula = stats::as.formula(paste0("cbind(", paste0(lhs, collapse = ","), ") ~ ", paste0(rhs, collapse = "+"))))
}
# getFormulaSides(z ~ x + y)
# getFormulaSides(cbind(z1, z2) ~ x + y)
# getFormulaSides(. ~ x + y)
# getFormulaSides(cbind(z1, z2) ~ .)
# getFormulaSides(. ~ x + y, names = c("z1", "z2", "x", "y"))
# getFormulaSides(cbind(z1, z2) ~ ., names = c("z1", "z2", "x", "y"))
blockdiag <- function(x, j, back = NULL) {
d <- dim(as.matrix(x))
if (!is.null(back) & (dim(back)[1] != d[1]*j || dim(back)[2] != d[2]*j)) {
warning("Wrong dimensions of background matrix. Set to Zero-Matrix. ")
back <- NULL
}
if (is.null(back)) {
X <- matrix(0, nrow = d[1] * j, ncol = d[2] * j)
} else {
X <- back
}
for (i in 0:(j-1)) {
X[(i*d[1]+1):((i+1)*d[1]), (i*d[2]+1):((i+1)*d[2])] <- x
}
X
}
# blockdiag(matrix(1:4, 2), 3)
# blockdiag(matrix(1:8, 2), 3)
# blockdiag(matrix(1:4, 2), 3, matrix(NA, nr = 6, nc = 6))
# blockdiag(matrix(1:4, 2), 3, matrix(NA, nr = 6, nc = 7))
blockdiag_list <- function(x, back = NULL) {
dims <- lapply(x, dim)
dim <- c(sum(sapply(dims, getElement, 1)), sum(sapply(dims, getElement, 2)))
if (!is.null(back) & (dim(back)[1] != dim[1] || dim(back)[2] != dim[2])) {
warning("Wrong dimensions of background matrix. Set to Zero-Matrix. ")
back <- NULL
}
if (is.null(back)) {
X <- matrix(0, nrow = dim[1], ncol = dim[2])
} else {
X <- back
}
pos <- list(
c(0, cumsum(sapply(dims, getElement, 1))),
c(0, cumsum(sapply(dims, getElement, 2)))
)
for (i in 1:length(x)) {
X[(pos[[1]][i]+1):pos[[1]][i+1], (pos[[2]][i]+1):pos[[2]][i+1]] <- x[[i]]
}
X
}
# blockdiag_list(list(matrix(1:4, 2), matrix(1:9, 3)))
# blockdiag_list(list(matrix(1:4, 2), matrix(1:8, 2)), back = matrix(NA, nr = 4, nc = 6))
removeAttributes <- function(x) {
attr(x, "source") <- NULL
attr(x, "class") <- NULL
attr(x, "order") <- NULL
attr(x, "distribution") <- NULL
attr(x, "leftrim") <- NULL
attr(x, "rightrim") <- NULL
attr(x, "computation.method") <- NULL
x
}
buildNames <- function(prefix, order, stations = NULL) {
if (is.null(stations) || length(stations) == 1) {
paste0(prefix, order)
} else {
paste0(rep(paste0(prefix, order), length(stations)), "_", rep(stations, each = length(order)))
}
}
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