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Statistics for spatial models

  • Carlo Gaetan
  • Xavier Guyon
Chapter
Part of the Springer Series in Statistics book series (SSS)

Abstract

In this chapter we present the main statistical methods used to deal with the three types of data seen in earlier chapters. As well as general statistical methods that can be applied to various structures (maximum likelihood, minimum contrast, least squares, estimation of generalized linear models, the method of moments), we have specific techniques for each type of structure: variogram clouds in geostatistics, conditional pseudo-likelihood, Markov random field coding, nearest-neighbor distances, composite likelihood for PPs, etc. We will present each method in turn.

Keywords

Ordinary Little Square Spatial Model Asymptotic Normality Weighted Little Square Generalize Little Square 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Dipartimento di StatisticaUniversità Ca’ Foscari VeneziaVenezialtaly
  2. 2.SAMOS Université Paris IParisFrance

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