predictKM {qle} | R Documentation |
predictKM
,wrapper for kriging the sample means of statistics
varKM
,calculate the kriging prediction variances
extract
,extract the results of kriging
predictKM(models, ...) varKM(models, ...) extract(X, type = c("mean", "sigma2", "weights"))
models |
list of covariance models, see |
... |
further arguments passed to function |
X |
kriging result |
type |
return type of results, see details below |
For a list of fitted covariance models the function predictKM predicts the sample means of statistics at (unsampled) points, calculates the prediction variances, if applicable, at these points and extracts the results. Note that, since we aim on predicting the "error free" value of the sample means, we use the smoothing kriging predictor as described in [2, Sec. 3.7.1].
The function extract either returns the predicted values, the prediction variances or the kriging weights for each point.
predictKM |
list of kriging predicted values |
varKM |
list of kriging prediction variances |
|
matrix of corresponding values (see details) |
data(normal) X <- as.matrix(qsd$qldata[,1:2]) p <- c("mu"=2,"sd"=1) # get simulated statistics at design X Tstat <- qsd$qldata[grep("^mean[.]",names(qsd$qldata))] # predict and extract predictKM(qsd$covT,p,X,Tstat) # prediction variances varKM(qsd$covT,p,X,Tstat)