drvkde {feature} | 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 |
vector of ranges for x |
binned |
TRUE if x is binned counts or FALSE (default) if x is data matrix |
se |
TRUE (default) computes standard error (SE) for kernel estimate or FALSE skips computing SE |
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.
This function doesn't need to be used directly as it called from
featureSignif
.
If se=TRUE
, it 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
.
Otherwise if
se=FALSE
, only x.grid
and est
are returned.
M.P. Wand wand@maths.unsw.edu.au
Wand, M.P. and Jones, M.C. (1995) Kernel Smoothing Chapman and Hall.