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Kriging with external drift in a Birnbaum–Saunders geostatistical model

  • Fabiana Garcia-Papani
  • Víctor Leiva
  • Fabrizio Ruggeri
  • Miguel A. Uribe-Opazo
Original Paper

Abstract

Spatial models to describe dependent georeferenced data are applied in different fields and, particularly, are used to analyze earth and environmental data. Most of these applications are carried out under Gaussian spatial models. The Birnbaum–Saunders distribution is a unimodal and positively skewed model which has received considerable attention in several areas, including earth and environmental sciences. In addition, theoretical arguments have been provided to justify its usage in the data modeling from these sciences, at least in the same settings where the lognormal distribution can be employed. This paper presents kriging with external drift based on a Birnbaum–Saunders spatial model. The maximum likelihood method is considered to estimate its parameters. The results obtained in the paper are illustrated by an experimental data set related to agricultural management. Specifically, in this illustration, the spatial variability of magnesium content in the soil as a function of calcium content is analyzed.

Keywords

Agricultural data analysis Cross-validation Maximum likelihood estimation Non-normal distributions R software Variogram models 

Notes

Acknowledgements

The authors thank the Editors and referees for their constructive comments on an earlier version of this manuscript which resulted in this improved version. This research work was partially supported by CNPq and CAPES grants from the Brazilian government, and by FONDECYT 1160868 grant from the Chilean government.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Postgraduate Program in Agricultural Engineering and Center of Exact Sciences and TechnologyUniversidade Estadual do Oeste do ParanáCascavelBrazil
  2. 2.School of Industrial EngineeringPontificia Universidad Católica de ValparaísoValparaísoChile
  3. 3.CNR-IMATIMilanoItaly

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