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## ' Similar to \code{\link[KrigInv]{computeQuickKrigcov}}, but without dataframe to matrix conversion
## ' for faster execution
## ' @title Quick computation of kriging covariances
## ' @param model A Kriging model of \code{\link[DiceKriging]{km}} class.
## ' @param integration.points p*d matrix of points for numerical integration in the X space.
## ' @param X.new The new point where we calculate kriging covariances. The calculated covariances
## ' are the covariances between this new point and all the integration points.
## ' @param precalc.data List containing precalculated data. This list is generated using the function
## ' \code{\link[KrigInv]{precomputeUpdateData}}
## ' @param F.newdata The value of the kriging trend basis function at point X.new
## ' @param c.newdata The (unconditional) covariance between X.new and the design points
## ' @details See \code{\link[KrigInv]{computeQuickKrigcov}} for more details
## '
## ' @return \code{TRUE} if the point should not be tested
## ' @export
computeQuickKrigcov2 <- function(model,integration.points,X.new, precalc.data, F.newdata , c.newdata){
# X.new <- as.matrix(X.new)
# if (model@d == 1){ integration.points <- as.matrix(integration.points) }
# colnames(integration.points) <- colnames(model@X)
c.xnew.integpoints <- covMat1Mat2(X1=integration.points,X2=X.new, object=model@covariance, nugget.flag=model@covariance@nugget.flag)
cov.std <- c.xnew.integpoints - crossprod(precalc.data$Kinv.c.olddata,c.newdata) #O(M.n) here
if (is.null(F.newdata))
{kn=cov.std
} else
{ second.member <- t(F.newdata - crossprod(c.newdata,precalc.data$Kinv.F))
cov.F <- precalc.data$first.member%*%second.member
kn <- cov.F+cov.std}
return(kn)
}
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