Hscv, Hscv.diag {ks} | R Documentation |
SCV bandwidth matrix for 2- to 6-dimensional data.
Hscv(x, pre="sphere", Hstart, binned=FALSE, bgridsize) Hscv.diag(x, pre="scale", Hstart, binned=FALSE, bgridsize)
x |
matrix of data values |
pre |
"scale" = pre-scaling, "sphere" = pre-sphering |
Hstart |
initial bandwidth matrix, used in numerical optimisation |
binned |
flag for binned kernel estimation |
bgridsize |
vector of binning grid sizes -
required only if binned=TRUE |
This SCV selector is a generalisation of the univariate SCV selector of Jones, Marron & Park (1991).
For d = 1, 2, 3, 4 and binned=TRUE
,
the density estimate is computed over a binning grid defined
by bgridsize
. Otherwise it's computed exactly.
For details on the pre-transformations in pre
, see
pre.sphere
and pre.scale
.
If Hstart
is not given then it defaults to
k*var(x)
where k = 4/(n*(d + 2))^(2/(d+ 4)), n = sample size, d = dimension of data.
SCV bandwidth matrix.
Jones, M.C., Marron, J.~S. & Park, B.U. (1991) A simple root n bandwidth selector. Annals of Statistics 19, 1919–1932.
Duong, T. & Hazelton, M.L. (2005) Cross-validation bandwidth matrices for multivariate kernel density estimation. Scandinavian Journal of Statistics. 32, 485-506.
data(unicef) Hscv(unicef) Hscv(unicef, binned=TRUE) Hscv.diag(unicef)