Recognition of the limitations of traditional hedonic models to account for spatial effects has led in recent years to the development and use of spatial econometric and statistical techniques in real estate applications. It seems appropriate, as the number of applications grows, to evaluate the relative ability of some newer approaches in terms of producing accurate spatial predictions. This a...

18 Tea fields emit large amounts of nitrous oxide (N2O) to the atmosphere. Obtaining accurate 19 estimations of N2O emissions from tea-planted soils is challenging due to strong spatial 20 variability. We examined the spatial variability of N2O emissions from a red-soil tea field in 21 Hunan province, China, on 22 April 2012 (in a wet season) using 147 static mini chambers 22 approximately regu...

The paper introduces a method of digital mapping of spatial distribution of soil typological units. It implements fuzzy k-means to classify the soil profile data (study area from the Považský Inovec Mountains, Slovakia) and regression-kriging with the selected digital terrain and remote sensing data to draw membership maps of soil typological units. Totally three soil typological units were ide...

Recently, Spöck and Pilz (2010), demonstrated that the spatial sampling design problem for the Bayesian linear kriging predictor can be transformed to an equivalent experimental design problem for a linear regression model with stochastic regression coefficients and uncorrelated errors. The stochastic regression coefficients derive from the polar spectral approximation of the residual process. ...

In the present paper, a Kriging-based metamodeling technique is used to minimize the risk of failure in a sheet metal forming process. The Krigingbased models are fitted to data that are obtained for larger experimental areas than the areas used in loworder polynomial regression metamodels. Therefore, computational time and memory requirement can be an obstacle for Kriging for data sets with ma...

Fast Parallel Kriging-Based Stepwise Uncertainty Reduction With Application to the Identification of an Excursion Set Clément Chevalier, David Ginsbourger, Julien Bect, Emmanuel Vazquez, Victor Picheny & Yann Richet a Institute of Mathematical Statistics and Actuarial Science University of Bern CH-3012 Bern, Switzerland (; ) b Department of Signal Processing & Electronic Systems Supelec, Gif-su...

Quasi-regression is introduced for approximation of functions on the unit cube in s dimensions. It is computationally eecient, compared to kriging, for problems requiring a large number of function evaluations. This paper describes how to implement quasi-regression and shows how to estimate the approximation error using the same data used to build the approximation. Four example functions are i...