This paper considers spatial data z(s1); Z(s2); ; Z(sn) collected at n locations, with the objective of predicting z(s0) at another location. The usual method of analysis for this problem is kriging, but here we introduce a new signal-plus-noise model whose essential feature is the identi cation of hot spots. The signal decays in relation to distance from hot spots. We show that hot spots can b...

This survey considers the optimization of simulated systems. The simulation may be either deterministic or random. The survey reflects the author’s extensive experience with simulationoptimization through Kriging (or Gaussian process) metamodels using a frequentist (non-Bayesian) approach. The analysis of Kriging metamodels may use bootstrapping. The survey discusses both parametric bootstrappi...

In this paper, results from three different interpolation techniques based on Geostatistics (ordinary kriging, kriging with external drift and conditional simulation) and one deterministic method (inverse distances) for mapping total monthly rainfall are compared. The study data set comprised total monthly rainfall from 1998 till 2001 corresponding to a maximum of 121 meteorological stations ir...

Finding new valuable sampling points and making these better distributed in the design space is key to determining approximate effect of Kriging. To this end, a high-precision Kriging modeling method based on hybrid criteria (HKM-HS) proposed solve problem. In HKM-HS method, two infilling strategies MSE (Mean Square Error) are optimized obtain candidate points. By maximizing (MMSE) model, it ca...

Bayesian kriging is a useful tool for estimating spatial distributions of metals; however, estimates are generally only verified statistically. In this study surface soil samples were collected on a uniform grid and analyzed for As, Cr, Pb, and Hg. The data were interpolated at individual locations by Bayesian kriging. Estimates were validated using a leave-one-out cross validation (LOOCV) stat...

Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolat...

We use stochastic kriging, a metamodeling technique, to speed up nested simulation of expected shortfall, a portfolio risk measure. Evaluating a risk measure of a portfolio that includes derivative securities may require nested Monte Carlo simulation. The outer level simulates financial scenarios and the inner level of simulation estimates the portfolio value given a scenario. Spatial metamodel...

In recent years, methods of fuzzy reasoning have been successfully developed for land evaluation. The accuracy of such land evaluation depends on the quality of weighing land characteristics with respect to their effects on crop production. This paper presents a spatially-based model of land suitability analysis. The main purposes were to (1) establish land suitability indices for irrigated whe...