Author(s):
Mendes, Armando B. ; Cardoso, Margarida G.M.S. ; Oliveira, Rui Carvalho
Date: 2005
Persistent ID: http://hdl.handle.net/10400.3/2179
Origin: Repositório da Universidade dos Açores
Subject(s): Spatial Data Analysis; Voronoi Diagrams; Influence Area; Discriminant Analysis; Classification Tree; Precision Index; Jackknife Validation; Dominance Analysis; Spatial Data Analysis; Spatial Data Analysis; Voronoi Diagrams; Voronoi Diagrams; Influence Area; Influence Area; Discriminant Analysis; Discriminant Analysis; Classification Tree; Classification Tree; Precision Index; Precision Index; Jackknife Validation; Jackknife Validation; Dominance Analysis; Dominance Analysis
Description
In this presentation a methodology is suggested for site assessment and site selection based in a data analysis framework. This framewo rk consists in tree steeps using different data analysis methods from cluster analysis, classification trees and regression analysis. The different variables selected in all the models used for the three steeps are compared and the spatial analysis data importance in site assessment is evaluated. For variable importance several easures can be used. In this text we use the discriminant power for the selection of profiling variables and a precision index for classification trees. Dominance analysis is used for the multiple regression models in the forecasting procedure. The advantage of this technique over other techniques as the standardized coefficients is that it overcomes some limitations of stepwise regression. The different measures of variable importance result in a clear pattern for the relevance of spatial analysis variables, being only dominated by the "trade area". So, spatial analysis resulting variables are of special importance in site assessment studies and the delimitation method used for their calculation is relevant in their usefulness.
