Nothing
falkMVUE <- function(est, omega, ks = NA){
#
# Calculate Falk's minimum variance unbiased tail index estimator, for a known endpoint.
#
# Input:
# - x : Vector of quantiles. If the ordinary Pickand estimator is to be calculated,
# x simply equals the vector of ordered observations.
# - gam : Known tail index.
#
# Kaspar Rufibach, 2010
#
n <- est$n
x <- est$xn
v1 <- 1:n*NA
v2 <- v1
if (omega < x[n]){
cat("omega must be greater than max(x)!")} else {
# calculate quantiles
c <- 1:n
q <- logcondens::quantilesLogConDens(ps = c / n, est)[, "quantile"]
k0 <- 2:(n - 1)
if (identical(NA, ks)){ks <- k0}
ks <- ks[(ks %in% k0)]
for (k in ks){
j <- 2:k
# Falks based on quantiles of log-concave
temp <- (omega - q[n-j+1]) / (omega - q[n-k])
v1[k] <- sum(log(temp)) / k
# Falks based on order statistics
temp <- (omega - x[n-j+1]) / (omega - x[n-k])
v2[k] <- sum(log(temp)) / k
}
res <- cbind("k" = 1:n, "logcon" = v1, "order" = v2)
return(res)}
}
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