Usage
lstseq.kern(dendat, hseq, N, lstree = NULL, level = NULL,
Q = NULL, kernel = "gauss", hw = NULL, algo = "leafsfirst", support = NULL)
Arguments
dendat
n*d matrix of real numbers; the data matrix
hseq
a vector of positive real numbers;
the sequence should be monotonic
N
vector of d positive integers; the dimension of the grid where the
kernel estimate will be evaluated; we evaluate the estimate on a regular
grid which contains the support of the kernel estimate
lstree
if NULL, then level set trees are not calculated
level
NULL or a real number between 0 and 1;
if NULL, then shape trees are not calculated;
if number, then it is the level in percents of the maximum
of the level sets for which the shape trees are calculated
Q
positive integer; needed only in the DynaDecompose algorithm, see
parameter "algo"; the number of levels in the level set trees
kernel
"epane" or "gauss"; the kernel is either the
Bartlett-Epanechnikov product kernel or the standard Gaussian
hw
positive integer; parameter for time localized kernel estimation;
gives the smoothing parameter for the temporal smoothing
algo
"leafsfirst" or "dynadecompose"
support
2*d vector of reals gives the d intervals of a
rectangular support; c(low1,upp1,...,lowd,uppd)