?? drvkde.rd
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\name{drvkde}\alias{drvkde}\title{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{ \item{x}{data matrix or matrix of binning counts} \item{drv}{vector of derivative indices} \item{bandwidth}{vector of bandwidths} \item{gridsize}{vector of grid sizes} \item{range.x}{list of vector of ranges for x} \item{binned}{TRUE if x is binned counts or FALSE if x is data matrix} \item{se}{flag for computing the standard error of kernel estimate} %%\item{estimate.positive}{flag for ensuring all estimate values are positive}}\value{ Returns a list with fields \code{x.grid} - grid points \cr \code{est} - kernel estimate of partial derivative of density function indicated by \code{drv}\cr \code{se} - estimate of standard error of \code{est} (if \code{se=TRUE}).}\details{The estimates and standard errors are computed over a grid of binned counts \code{x.grid}. If the binned counts are not supplied then they are computed inside this function. If \code{gridsize} and \code{range.x} are not supplied, they are computed inside this function.}\examples{## univariatex <- rnorm(100)fhat <- drvkde(x=x, drv=0, bandwidth=0.1) ## KDE of ffhat1 <- drvkde(x=x, drv=1, bandwidth=0.1) ## KDE of df/dx}\references{ Wand, M.P. and Jones, M.C. (1995) \emph{Kernel Smoothing}. Chapman \& Hall/CRC, London.} \author{M.P. Wand}\keyword{smooth}
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