Compute h(alpha) which is the size of the subsamples to be used
for MCD and LTS. Given
For h == floor(n+p+1)/2
; for the general
case, it's simply
n2 <- (n+p+1) %/% 2; floor(2*n2 - n + 2*(n-n2)*alpha)
.
h.alpha.n(alpha, n, p)
numeric vector of
fraction, numeric (vector) in [0.5, 1], see, e.g.,
covMcd
.
integer (valued vector), the sample size.
integer (valued vector), the dimension.
covMcd
and ltsReg
which are
defined by h.alpha.n
.
n <- c(10:20,50,100)
p <- 5
## show the simple "alpha = 1/2" case:
cbind(n=n, h= h.alpha.n(1/2, n, p), n2p = floor((n+p+1)/2))
## alpha = 3/4 is recommended by some authors :
n <- c(15, 20, 25, 30, 50, 100)
cbind(n=n, h= h.alpha.n(3/4, n, p = 6))
Run the code above in your browser using DataLab