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Author (up) Garcia-Papani, F.; Uribe-Opazo, M.A.; Leiva, V.; Aykroyd, R.G. pdf  doi
  Title Birnbaum-Saunders spatial modelling and diagnostics applied to agricultural engineering data Type
  Year 2017 Publication Stochastic Environmental Research And Risk Assessment Abbreviated Journal Stoch. Environ. Res. Risk Assess.  
  Volume 31 Issue 1 Pages 105-124  
  Keywords Asymmetric distributions; Local influence; Matern model; Maximum likelihood methods; Monte Carlo simulation; Non-normality; R software; Spatial data analysis  
  Abstract Applications of statistical models to describe spatial dependence in geo-referenced data are widespread across many disciplines including the environmental sciences. Most of these applications assume that the data follow a Gaussian distribution. However, in many of them the normality assumption, and even a more general assumption of symmetry, are not appropriate. In non-spatial applications, where the data are uni-modal and positively skewed, the Birnbaum-Saunders (BS) distribution has excelled. This paper proposes a spatial log-linear model based on the BS distribution. Model parameters are estimated using the maximum likelihood method. Local influence diagnostics are derived to assess the sensitivity of the estimators to perturbations in the response variable. As illustration, the proposed model and its diagnostics are used to analyse a real-world agricultural data set, where the spatial variability of phosphorus concentration in the soil is considered-which is extremely important for agricultural management.  
  Address [Garcia-Papani, Fabiana; Uribe-Opazo, Miguel Angel] Univ Estadual Oeste Parana, Postgrad Program Agr Engn, Ctr Exact Sci & Technol, Cascavel, PR, Brazil, Email:;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1436-3240 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000394278600008 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 704  
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