leaveOneOut.km {DiceKriging} | R Documentation |
Cross validation by leave-one-out for a km
object.
leaveOneOut.km(model, type)
model |
an object of class "km". |
type |
a character string corresponding to the kriging family, to be chosen between simple kriging ("SK"), or universal kriging ("UK"). At this stage, only "UK" is available. |
Leave-one-out consists of computing the prediction at a design point when the corresponding observation is removed from the learning set (and this, for all design points).
A list composed of:
mean |
a vector of length n. The ith coordinate is equal to the kriging mean (including the trend) at the ith observation number when removing it from the learning set, |
sd |
a vector of length n. The ith coordinate is equal to the kriging standard deviation at the ith observation number when removing it from the learning set, |
where n is the total number of observations.
Kriging parameters are not re-estimated when removing one observation. With few points, the re-estimated values can be far from those obtained with the entire learning set.
O. Roustant, D. Ginsbourger, Ecole des Mines de St-Etienne.
N.A.C. Cressie (1993), Statistics for spatial data, Wiley series in probability and mathematical statistics.
J.D. Martin and T.W. Simpson (2005), Use of kriging models to approximate deterministic computer models, AIAA Journal, 43 no. 4, 853-863.
M. Schonlau (1997), Computer experiments and global optimization, Ph.D. thesis, University of Waterloo.