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 list of vector of ranges for x
binned flag to indicate: TRUE = x is binned counts or FALSE = x is data matrix. Default is TRUE
se flag for computing standard error of kernel estimate. Default is TRUE

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.

If gridsize and range.x are not supplied, they are computed inside this function.

This function doesn't need to be used directly as it called from featureSignif.

Value

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).

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

Examples

## univariate
data(earthquake)
eq3 <- -log10(-earthquake[,3])
fhat <- drvkde(x=eq3, drv=0, bandwidth=0.1)    ## KDE of f
fhat1 <- drvkde(x=eq3, drv=1, bandwidth=0.1)   ## KDE of df/dx

## trivariate
data(earthquake)
earthquake[,3] <- -log10(-earthquake[,3])
fhat <- drvkde(x=earthquake, drv=c(0,0,0), bandwidth=c(0.04,0.04,0.05),
               se=FALSE)     ## KDE of f
                                              
fhat212 <- drvkde(x=earthquake, drv=c(2,1,2), bandwidth=c(0.04,0.04,0.05),
                  se=FALSE)  ## KDE of d^3 f/ dx^2 dy dz^2

[Package feature version 1.1-11 Index]