Generalized Linear Spatial Models to Predict Slate Exploitability

نویسندگان

  • Angeles Saavedra
  • Javier Taboada
  • María Araújo
  • Eduardo Giráldez
چکیده

The aim of this research was to determine the variables that characterize slate exploitability and to model spatial distribution. A generalized linear spatialmodel (GLSMs)was fitted in order to explore relationship between exploitability and different explanatory variables that characterize slate quality.Modelling the influence of these variables and analysing the spatial distribution of themodel residuals yielded a GLSM that allows slate exploitability to be predicted more effectively than when using generalized linear models (GLM), which do not take spatial dependence into account. Studying the residuals and comparing the prediction capacities of the two models lead us to conclude that the GLSM is more appropriate when the response variable presents spatial distribution.

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عنوان ژورنال:
  • J. Applied Mathematics

دوره 2013  شماره 

صفحات  -

تاریخ انتشار 2013