Generalized Linear Spatial Models to Predict Slate Exploitability
The aim of this research was to determine the variables that characterize slate exploitability and to model spatial distribution. A generalized linear spatial model (GLSMs) was fitted in order to explore relationship between exploitability and different explanatory variables that characterize slate...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
|
| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2013/531062 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832555890943721472 |
|---|---|
| author | Angeles Saavedra Javier Taboada María Araújo Eduardo Giráldez |
| author_facet | Angeles Saavedra Javier Taboada María Araújo Eduardo Giráldez |
| author_sort | Angeles Saavedra |
| collection | DOAJ |
| description | The aim of this research was to determine the variables that characterize slate exploitability and to model spatial distribution. A generalized linear spatial model (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 the model 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. |
| format | Article |
| id | doaj-art-ec318122888f4e27a811761d10a902b1 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-ec318122888f4e27a811761d10a902b12025-02-03T05:46:54ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/531062531062Generalized Linear Spatial Models to Predict Slate ExploitabilityAngeles Saavedra0Javier Taboada1María Araújo2Eduardo Giráldez3Department of Statistics, University of Vigo, 36310 Vigo, SpainDepartment of Natural Resources, University of Vigo, 36310 Vigo, SpainDepartment of Natural Resources, University of Vigo, 36310 Vigo, SpainDepartment of Natural Resources, University of Vigo, 36310 Vigo, SpainThe aim of this research was to determine the variables that characterize slate exploitability and to model spatial distribution. A generalized linear spatial model (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 the model 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.http://dx.doi.org/10.1155/2013/531062 |
| spellingShingle | Angeles Saavedra Javier Taboada María Araújo Eduardo Giráldez Generalized Linear Spatial Models to Predict Slate Exploitability Journal of Applied Mathematics |
| title | Generalized Linear Spatial Models to Predict Slate Exploitability |
| title_full | Generalized Linear Spatial Models to Predict Slate Exploitability |
| title_fullStr | Generalized Linear Spatial Models to Predict Slate Exploitability |
| title_full_unstemmed | Generalized Linear Spatial Models to Predict Slate Exploitability |
| title_short | Generalized Linear Spatial Models to Predict Slate Exploitability |
| title_sort | generalized linear spatial models to predict slate exploitability |
| url | http://dx.doi.org/10.1155/2013/531062 |
| work_keys_str_mv | AT angelessaavedra generalizedlinearspatialmodelstopredictslateexploitability AT javiertaboada generalizedlinearspatialmodelstopredictslateexploitability AT mariaaraujo generalizedlinearspatialmodelstopredictslateexploitability AT eduardogiraldez generalizedlinearspatialmodelstopredictslateexploitability |