drvkde {ks} | R Documentation |
Compute kernel density derivative estimates and standard errors for multivariate data.
drvkde(x, drv, bandwidth, gridsize, range.x, binned=FALSE, se=TRUE)
x |
data matrix or matrix of binning counts |
drv |
vector of derivative indices |
bandwidth |
vector of bandwidths |
gridsize |
vector of grid sizes |
range.x |
list of vector of ranges for x |
binned |
TRUE if x is binned counts or FALSE if x is data matrix |
se |
flag for computing the standard error of kernel estimate |
The estimates and standard errors are computed over a grid of binned counts
x.grid
. If the binned counts are not supplied then they are computed
inside this function.
If gridsize
and range.x
are not supplied, they are
computed inside this function.
Returns a list with fields
x.grid
- grid points
est
- kernel estimate of partial derivative of density function
indicated by drv
se
- estimate of standard error of est
(if se=TRUE
).
M.P. Wand
Wand, M.P. and Jones, M.C. (1995) Kernel Smoothing. Chapman & Hall/CRC, London.
## univariate x <- rnorm(100) fhat <- drvkde(x=x, drv=0, bandwidth=0.1) ## KDE of f fhat1 <- drvkde(x=x, drv=1, bandwidth=0.1) ## KDE of df/dx