Nothing
################################
#### Kernel density estimation of circular data with a von Mises kernel
#### Tsagris Michail 2/2015
#### mtsagris@yahoo.gr
#### Tuning the bandwidth
################################
vmkde.tune <- function(u, low = 0.1, up = 1, rads = TRUE) {
## u is the data
n <- length(u) ## sample size
## if the data are in degrees we transform them into radians
if ( !rads ) u <- u/180 * pi
x <- cbind( cos(u), sin(u) )
disa <- tcrossprod(x)
expa <- exp(disa)
diag(expa) <- - Inf ## we do not want the diagonal elements
con <- 2 * (n - 1) * pi
funa <- function(h) {
A <- expa^h
f <- Rfast::rowsums( A )
sum( log(f) ) - n * log( besselI(h, 0) )
}
bar <- optimize(funa, c(low, up), maximum = TRUE)
res <- c( bar$maximum, bar$objective/n - log(con) )
names(res) <- c("Optimal h", "cv")
res
}
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