Kernel functional estimate
Kernel functional estimate for 1- to 6-dimensional data.
kfe(x, G, deriv.order, inc=1, binned, bin.par, bgridsize, deriv.vec=TRUE, add.index=TRUE, verbose=FALSE) Hpi.kfe(x, nstage=2, pilot, pre="sphere", Hstart, binned=FALSE, bgridsize, amise=FALSE, deriv.order=0, verbose=FALSE, optim.fun="optim") Hpi.diag.kfe(x, nstage=2, pilot, pre="scale", Hstart, binned=FALSE, bgridsize, amise=FALSE, deriv.order=0, verbose=FALSE, optim.fun="optim") hpi.kfe(x, nstage=2, binned=FALSE, bgridsize, amise=FALSE, deriv.order=0)
x |
vector/matrix of data values |
nstage |
number of stages in the plug-in bandwidth selector (1 or 2) |
pilot |
"dscalar" = single pilot bandwidth (default) |
pre |
"scale" = |
Hstart |
initial bandwidth matrix, used in numerical optimisation |
binned |
flag for binned estimation |
bgridsize |
vector of binning grid sizes |
amise |
flag to return the minimal scaled PI value |
deriv.order |
derivative order |
verbose |
flag to print out progress information. Default is FALSE. |
optim.fun |
optimiser function: one of |
G |
pilot bandwidth matrix |
inc |
0=exclude diagonal, 1=include diagonal terms in kfe calculation |
bin.par |
binning parameters - output from |
deriv.vec |
flag to compute duplicated partial derivatives in the vectorised form. Default is FALSE. |
add.index |
flag to output derivative indices matrix. Default is true. |
Hpi.kfe
is the optimal plug-in bandwidth for r-th order kernel functional estimator
based on the unconstrained pilot selectors of Chacon & Duong (2010).
hpi.kfe
is the 1-d equivalent, using the formulas from
Wand & Jones (1995, p.70).
kfe
does not usually need to be called explicitly by the user.
Plug-in bandwidth matrix for r-th order kernel functional estimator.
Chacon, J.E. & Duong, T. (2010) Multivariate plug-in bandwidth selection with unconstrained pilot matrices. Test, 19, 375-398.
Wand, M.P. & Jones, M.C. (1995) Kernel Smoothing. Chapman & Hall/CRC, London.
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