Several authors have proposed nonparametric semivariogram estimators. Shapiro & Botha (1991) did so by application of Bochner’s theorem and Cherry, Banfield & Quimby (1996) further investigated this technique where it performed favorably against parametric estimators even when data were generated under the parametric model. While this approach is sound, it lacks nugget estimation which is essen...

ABSTRACT- The information on the spatial properties of soil is vital to improve soil management and to increase the crop productivity. Geostatistical analysis technique is one of the most important methods for determining the spatial properties of soil. The aim of this study was to investigate spatial variability of soil chemical and physical attributes for field management in eastern Shiraz, I...

Kriging is one of the most often used prediction methods in spatial data analysis. This paper examines which steps of the underlying algorithms can be performed in parallel on a PVM cluster. It will be shown, that some properties of the so called kriging equations can be used to improve the parallelized version of the algorithm. The implementation is based on R and PVM. An example will show the...

PEST is a numerical algorithm developed for the simulation in a rectangular R 2 or R 3 domain of a stochastic, isotropic, scalar eld which is conditioned pointwise to a set of measurements. The eld is characterized by heterogeneity variation described either by a two point covariance function C(r) or semivariogram (r) for pairs of points separated by distance r. Numerical examples using PEST ar...