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\name{layerStats}
\alias{layerStats}
\title{Correlation and (weighted) covariance}
\description{
Compute correlation and (weighted) covariance for multi-layer Raster objects. Like \code{\link{cellStats}} this function returns a few values, not a Raster* object (see \code{\link{Summary-methods}} for that).
}
\usage{
layerStats(x, stat, w, asSample=TRUE, na.rm=FALSE, ...)
}
\arguments{
\item{x}{RasterStack or RasterBrick for which to compute a statistic}
\item{stat}{Character. The statistic to compute: either 'cov' (covariance), 'weighted.cov' (weighted covariance), or 'pearson' (correlation coefficient)}
\item{w}{RasterLayer with the weights (should have the same extent, resolution and number of layers as \code{x}) to compute the weighted covariance}
\item{asSample}{Logical. If \code{TRUE}, the statistic for a sample (denominator is \code{n-1}) is computed, rather than for the population (denominator is \code{n})}
\item{na.rm}{Logical. Should missing values be removed?}
\item{...}{Additional arguments (none implemetned)}
}
\value{
List with two items: the correlation or (weighted) covariance matrix, and the (weighted) means.
}
\author{Jonathan A. Greenberg & Robert Hijmans. Weighted covariance based on code by Mort Canty}
\references{
For the weighted covariance:
\itemize{
\item {Canty, M.J. and A.A. Nielsen, 2008. Automatic radiometric normalization of multitemporal satellite imagery with the iteratively re-weighted MAD transformation. Remote Sensing of Environment 112:1025-1036.}
\item {Nielsen, A.A., 2007. The regularized iteratively reweighted MAD method for change detection in multi- and hyperspectral data. IEEE Transactions on Image Processing 16(2):463-478.}
}
}
\seealso{
\code{\link{cellStats}}, \code{\link{cov.wt}}, \code{\link[raster]{weighted.mean}}
}
\examples{
b <- brick(system.file("external/rlogo.grd", package="raster"))
layerStats(b, 'pearson')
layerStats(b, 'cov')
# weigh by column number
w <- init(b, v='col')
layerStats(b, 'weighted.cov', w=w)
}
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