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...

Two geostatistical methods for history matching are presented. Both rely on the sequential simulation principle for generating geologically sound realizations. The first method relies on perturbing the sequential simulation through the perturbation of the conditional distribution models; the second method relies on the perturbation of random numbers. We show that both approaches are general in ...

Title of dissertation: SCALABLE LEARNING FOR GEOSTATISTICS AND SPEAKER RECOGNITION Balaji Vasan Srinivasan Doctor of Philosophy, 2011 Thesis directed by: Professor Ramani Duraiswami Department of Computer Science With improved data acquisition methods, the amount of data that is being collected has increased several fold. One of the objectives in data collection is to learn useful underlying pa...

This paper explores the potential of infrared thermography and geostatistics in animal production presents results application combination these techniques, contributing significantly to efforts obtain animals’ responses environments which they are located thereby ensuring improvements productivity welfare. The objective was verify variability surface temperature pigs submitted different climat...

Traditional geostatistical space-time geostatistics is not able to take account of the generally strongly non-linear dynamics of multivariate space-time processes. To this effect physico-chemical transport models are in general more suitable. However, as the latter do not fully master the complexity of the processes they attempt to describe, either because of simplifying hypotheses or because t...

Spatial data analysis focuses on both attribute and locational information. Local analyses deal with differences across space whereas global analyses deal with similarities across space. This paper addresses an experimental comparative study to analyse the spatial data by some weighted local regression models. Five local regression models have been developed and their estimation capacities have...

Geostatistics and GIS were used to analyze the spatial variability of the soil water characteristics in western semiarid area of Heilongjiang province. Irrigation management zone was established based on spatial distribution of the soil water characteristics and actual condition of the study area. Sampling by layered sampling method and calculating of the rational sampling number by best distri...

Geostatistics combined with GIS spatial technology was applied to analyze the time and spatial variability of pH in topsoil(0-20cm) for planted tobacco region in Sanmenxia district. The results indicated that the pH value range form 6.5 to 8.8 and meet to the need of produce high quality tobacco, but the pH value of partial region is high. The pH value accord with logarithm normal distribution,...

Geostatistics is a distinctive methodology within the field of spatial statistics. In the past, it has been linked to particular problems (e.g., spatial interpolation by kriging) and types of spatial data (attributes defined on continuous space). It has been used more by physical than human geographers because of the nature of their types of data. The approach taken by geostatisticians has seve...