locpol (version 0.8.0)

denCVBwSelC: CV bandwidth selector for density

Description

Computes Cross Validation bandwidth selector for the Parzen--Rosenblatt density estimator...

Usage

denCVBwSelC(x, kernel = gaussK, weig = rep(1, length(x)),
            interval = .lokestOptInt)

Value

A numeric value with the bandwidth.

Arguments

x

vector with data points.

kernel

Kernel used to perform the estimation, see Kernels.

weig

Vector of weights for observations.

interval

A range of values where to look for the bandwidth parameter.

Author

Jorge Luis Ojeda Cabrera.

Details

The selector is implemented using its definition.

References

Fan, J. and Gijbels, I. Local polynomial modelling and its applications\/. Chapman & Hall, London (1996).

Wand, M.~P. and Jones, M.~C. Kernel smoothing\/. Chapman and Hall Ltd., London (1995).

See Also

bw.nrd0, dpik.

Examples

stdy <- function(size=100,rVar=rnorm,dVar=dnorm,kernel=gaussK,x=NULL)
{
	if( is.null(x) ) x <- rVar(size)
	Tc <- system.time( dbwc <- denCVBwSelC(x,kernel) )[3]
	ucvT <- system.time( ucvBw <- bw.ucv(x,lower=0.00001,upper=2.0) )[3]
	nrdT <- system.time( nrdBw <- bw.nrd(x) )[3]
	{
		xeval <- seq( min(x)+dbwc , max(x)-dbwc ,length=50)
		hist(x,probability=TRUE)
		lines(xeval,trueDen <- dVar(xeval),col="red")
		lines(density(x),col="cyan")
		xevalDenc <- PRDenEstC(x,xeval,dbwc,kernel)
		dencMSE <- mean( (trueDen-xevalDenc)^2 )
		xevalucvDen <- PRDenEstC(x,xeval,ucvBw,kernel)
		ucvMSE <- mean( (trueDen-xevalucvDen)^2 )
		xevalDenNrd <- PRDenEstC(x,xeval,nrdBw,kernel)
		nrdMSE <- mean( (trueDen-xevalDenNrd)^2 )
		lines(xevalDenc,col="green")
		lines(xevalucvDen,col="blue")
		lines(xevalDenNrd,col="grey")
	}
	return( cbind(  bwVal=c(evalC=dbwc,ucvBw=ucvBw,nrdBw=nrdBw),
				mse=c(dencMSE,ucvMSE,nrdMSE),
				time=c(Tc,ucvT,nrdT) ) )
}
stdy(100,kernel=gaussK)
stdy(100,rVar=rexp,dVar=dexp,kernel=gaussK)
##	check stdy with other kernel, distributions