drvkde {feature}R Documentation

Kernel density derivative estimation

Description

Compute kernel density derivative estimates and standard errors for multivariate data.

Usage

drvkde(x,drv,bandwidth,gridsize,range.x,binned=FALSE,se=TRUE)

Arguments

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

Details

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.

Value

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.

Author(s)

M.P. Wand wand@maths.unsw.edu.au

References

Wand, M.P. and Jones, M.C. (1995) Kernel Smoothing Chapman and Hall.

See Also

featureSignif


[Package feature version 1.1-4 Index]