
spatial
 Referenced in 206 articles
[sw04502]
 spatial: Functions for Kriging and Point Pattern Analysis , Functions for kriging and point pattern analysis...

DACE
 Referenced in 108 articles
[sw04715]
 Matlab toolbox for working with kriging approximations to computer models. Typical use of this software ... construct a kriging approximation model based on data from a computer experiment ... evaluate the computer model for constructing the kriging approximation...

SPOT
 Referenced in 46 articles
[sw06347]
 CART and random forest; Gaussian process models (Kriging), and combinations of di erent metamodeling approaches...

FRK
 Referenced in 35 articles
[sw19172]
 package FRK. Fixed Rank Kriging is a tool for spatial/spatiotemporal modelling and prediction with large...

DiceKriging
 Referenced in 19 articles
[sw07783]
 DiceKriging: Kriging methods for computer experiments Estimation, validation and prediction of kriging models. Important functions...

DiceOptim
 Referenced in 17 articles
[sw07784]
 DiceOptim: Krigingbased optimization for computer experiments Expected Improvement. EGO algorithm. Multipoints EI and parallelized ... Constant Liars. Criteria and algorithms for Noisy Krigingbased Optimization , including...

Gstat
 Referenced in 9 articles
[sw04488]
 models (anisotropy coefficients are not fitted automatically). Kriging and (sequential) conditional simulation are done under ... this model include ordinary and simple kriging, ordinary or simple cokriging, universal kriging, external drift ... kriging, Gaussian conditional or unconditional simulation or cosimulation. In addition, variables may share trend coefficients...

AKMCS
 Referenced in 7 articles
[sw18303]
 active learning reliability method combining Kriging and Monte Carlo Simulation. An important challenge in structural ... researchers in the last decades. However, recently, Kriging, originated from geostatistics, have emerged in reliability ... analysis. Widespread in optimisation, Kriging has just started to appear in uncertainty propagation ... approach based on Monte Carlo Simulation and Kriging metamodel to assess the reliability of structures...

EnviroStat
 Referenced in 12 articles
[sw11048]
 devoted to techniques that are known as kriging. The third part presents the fully general...

RandomFields
 Referenced in 11 articles
[sw08188]
 extreme value random fields; conditional simulation; kriging; maximum likelihood estimation...

fields
 Referenced in 7 articles
[sw08187]
 methods include cubic, and thin plate splines, Kriging and compact covariances for large data sets ... splines and Kriging methods are supporting by functions that can determine the smoothing parameter (nugget...

SURROGATES
 Referenced in 10 articles
[sw07575]
 design, Doptimal and maxmin designs. Surrogates: kriging, polynomial response surface, radial basis neural network...

AQUARS
 Referenced in 6 articles
[sw07570]
 mesh adaptive direct search (MADS) combined with kriging. The results show that the AQUARS methods ... MLSL coupled to MADS with kriging on the watershed calibration problem...

gstat
 Referenced in 8 articles
[sw08293]
 ordinary and universal point or block (co)kriging, sequential Gaussian or indicator (co)simulation; variogram...

DECLUS
 Referenced in 5 articles
[sw13524]
 compared to polygonal declustering and global kriging...

Emlk2d
 Referenced in 2 articles
[sw13516]
 spatial estimation using empirical maximum likelihood kriging. The authors describe a Fortran90 program ... empirical maximum likelihood kriging. More efficient estimates are obtained by solving the estimation problem ... experimental data), where the simple kriging estimate is equivalent to the maximum likelihood estimate...

geofd
 Referenced in 2 articles
[sw08390]
 package geofd which implements ordinary kriging prediction for this type of data. Initially the curves ... parameters for performing prediction by ordinary kriging at unsampled locations are by estimated solving...

ooDACE
 Referenced in 1 article
[sw12876]
 ooDACE toolbox: a flexible objectoriented Kriging implementation. When analyzing data from computationally expensive simulation ... space exploration, sensitivity analysis, visualization and optimization. Kriging is a popular surrogate modeling technique used ... Computer Experiments (DACE). Hence, the past decade Kriging has been the subject of extensive research ... many extensions have been proposed, e.g., coKriging, stochastic Kriging, blind Kriging, etc. However...

UQLab
 Referenced in 3 articles
[sw19740]
 polynomial chaos expansions, Gaussian process modelling, a.k.a. Kriging, lowrank tensor approximations), rare event estimation...

Stochastic kriging
 Referenced in 1 article
[sw12891]
 Stochastic kriging is a metamodeling methodology developed for stochastic simulation experiments; it is based ... highly successful kriging method for the design and analysis of computer experiments. Stochastic kriging distinguishes ... also based on spatial correlation concepts. Stochastic kriging facilitates adaptive, sequential experiment designs that systematically ... userspecified level. The stochastic kriging Matlab software available from this web site is distributed...