When analyzing data from computationally expensive simulation codes, surrogate modeling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualization and optimization. Kriging is a popular surrogate modeling technique used for the Design and Analysis of Computer Experiments (DACE). Hence, the past decade Kriging has been the subject of extensiv...

Kriging is a useful method for developing metamodels for product design optimization. The most popular kriging method, known as ordinary kriging, uses a constant mean in the model. In this article, a modified kriging method is proposed, which has an unknown mean model. Therefore it is called blind kriging. The unknown mean model is identified from experimental data using a Bayesian variable sel...

1. Abstract Over three decades, metamodeling has been widely applied to design optimization problems to build a surrogate model of computation-intensive engineering models. The Kriging method has gained significant interests for developing the surrogate model. However, traditional Kriging methods, including the ordinary Kriging and the universal Kriging, use fixed polynomials basis functions to...

This paper develops a new modified Bayesian Kriging (MBKG) surrogate modeling method for problems in which simulation analyses are inherently noisy and thus standard Kriging approaches fail to properly represent the responses. The purpose is to develop a method that can be used to carry out reliability analysis to predict probability of failure. The formulation of the MBKG surrogate modeling me...

This paper introduces the gstat package for the S language (R, S-PLUS). The package provides multivariable geostatistical modelling, prediction and simulation, as well as several visualisation functions. Gstat (http://www. gstat.org) was started 10 years ago and was released under the GPL in 1996; it is closely linked to several GIS systems. It was not initially written for teaching purposes, b...

This paper discusses advantages and shortcomings of the S environment for multivariable geostatistics, in particular when extended with the gstat package, an extension package for the S environments (R, S-Plus). The gstat S package provides multivariable geostatistical modelling, prediction and simulation, as well as several visualisation functions. In particular, it makes the calculation, simu...

Metamodelling offers an efficient way to imitate the behaviour of computationally expensive simulators. Kriging based metamodels are popular in approximating computation-intensive simulations of deterministic nature. Irrespective of the existence of various variants of Kriging in the literature, only a handful of Kriging implementations are publicly available and most, if not all, free librarie...

In the practice of interpolating near-surface soil moisture measured by a wireless sensor network (WSN) grid, traditional Kriging methods with auxiliary variables, such as Co-kriging and Kriging with external drift (KED), cannot achieve satisfactory results because of the heterogeneity of soil moisture and its low correlation with the auxiliary variables. This study developed an Extended Krigin...

When analysing data from computationally expensive simulation codes or process measurements, surrogate modelling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualisation and optimisation. Kriging is a popular surrogate modelling technique for data based on deterministic computer experiments. There exist several types of Kriging, mostly dif...