The Mat ́ern correlation function provides great flexibility for modeling spatially correlated random processes in two dimensions, in particular via a smoothness parameter, whose estimation allows data to determine the degree of smoothness of a spatial process. The extension to include anisotropy provides a very general and flexible class of spatial covariance functions that can be used in a mod...

A utilização de modelos matemáticos e avaliação da geoestatística determinação do domínio solo é uma estratégia importância fundamental para os planejamentos agropecuários ambientais, principalmente em áreas agricultura familiar incorporadas nos microbacias hidrográficas. Desta forma, este trabalho objetivou estimar o potencial método seleção métodos solos microbacia mapeamento dados estatístic...

Many applications in spatial statistics, geostatistics and image analysis require efficient techniques for sampling from large Gaussian Markov random fields (GMRFs). A suite of methods, based on the Cholesky decomposition, for sampling from GMRFs, sampling conditioned on a set of linear constraints, and computing the likelihood were presented by Rue (2001). In this paper, we present an alternat...

Two robust approaches to principal component analysis and factor analysis are presented. The different methods are compared, and properties are discussed. As an application we use a large geochemical data set which was analyzed in detail by univariate (geo-)statistical methods. We explain the advantages of applying robust multivariate methods.

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...

The aim of this study is to explore the relationship between, transport, land-use and air quality and mapping of air pollutants by means of spatial information sciences, which would provide useful information for decision-makers. Integrated transport, land-use and air quality monitoring are prioritized especially in metropolitan areas. The complexity is straight forward, since data, indicators,...