Given the above model of stationary random spatial effects { ( ) : } s s R   , our ultimate objective is to apply these concepts to spatial models involving global trends, ( ) s  , i.e., to spatial stochastic models of the form, ( ) ( ) ( ) , Y s s s s R      . In continuous spatial data analysis, the most fully developed models of this type focus on spatial prediction, where values of ...

In this paper, pipelining concepts is adopted to increase the processing speed of image scaling algorithms. The proposed algorithm consists of pipelining stages along with a linear space-variant edge detector, a low complicacy sharpening spatial filter, and a simplified bilinear interpolation. The linear space-edge detector is used to discover the image edges by a lowcost catching technique. Th...

During recent years, oak decline has been widely spread across Brant’s oak (Quercus Brantii Lindl.) stands in the Zagros Mountains, Western Iran, which caused large-area forest dieback in several sites. Mapping the intensity and spatial distribution of forest dieback is essential for developing management and control strategies. This study evaluated a range of geostatistical and interpolation m...

In order to estimate rainfall magnitude at unmeasured locations, this entry to the Spatial Interpolation Comparison of 1997 (SIC'97) used 2-dimensional, anisotropic, inverse-distance weighting interpolator (IDW), with cross-validation as a method of optimizing the interpolator's parameters. A jackknife resampling was then used to reduce bias of the predictions and estimate their uncertainty. Th...

Two forms of spatial interpolation, the interpolation of point and areal data, are distinguished. Traditionally, point interpolation is applied to isarithmic, that is, contour mapping and areal interpolation to isopleth mapping. Recently, areal interpolation techniques have been used to obtain data for a set of administrative or political districts from another set of districts whose boundaries...

Managing and hedging the risks associated with Variable Annuity (VA) products requires intraday valuation of key risk metrics for these products. The complex structure of VA products and computational complexity of their accurate evaluation has compelled insurance companies to adopt Monte Carlo (MC) simulations to value their large portfolios of VA products. Because the MC simulations are compu...