Hscv, Hscv.diag, hscv {ks} | R Documentation |
SCV bandwidth for 1- to 6-dimensional data.
Hscv(x, pre="sphere", Hstart, binned=FALSE, bgridsize) Hscv.diag(x, pre="scale", Hstart, binned=FALSE, bgridsize) hscv(x, nstage=2, binned=TRUE, bgridsize, plot=FALSE)
x |
vector or 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 |
nstage |
number of stages in the SCV bandwidth selector (1 or 2) (1-d only) |
plot |
flag to display plot of SCV(h) vs h (1-d only) |
hsv
is the univariate SCV
selector of Jones, Marron & Park (1991). Hscv
is a
multivariate generalisation of this.
For d = 1, the selector hscv
is not always stable for large
sample sizes with binning.
Examine the plot from hscv(, plot=TRUE)
to
determine the appropriate smoothness of the SCV function. Any
non-smoothness is due to the discretised nature of binned estimation.
For d = 1, 2, 3, 4 and binned=TRUE
, the
estimates are 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.
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.diag(unicef, binned=TRUE) hscv(unicef[,1])