| 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.