STANOVA: a smoothed-ANOVA-based model for spatio-temporal disease mapping
| Autor: | Francisco Torres-Avilés, Miguel A. Martinez-Beneito |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Multivariate statistics
Environmental Engineering business.industry Computer science Computational intelligence Pattern recognition Random effects model Orthogonal basis Statistics Environmental Chemistry Analysis of variance Artificial intelligence Safety Risk Reliability and Quality business Smoothing General Environmental Science Water Science and Technology Parametric statistics |
| Zdroj: | STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT r-FISABIO: Repositorio Institucional de Producción Científica Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO) r-FISABIO. Repositorio Institucional de Producción Científica instname |
| ISSN: | 1436-3259 1436-3240 |
| Popis: | Spatio-temporal disease mapping can be viewed as a multivariate disease mapping problem with a given order of the geographic patterns to be studied. As a consequence, some of the techniques in multivariate literature could also be used to build spatio-temporal models. In this paper we propose using the smoothed ANOVA multivariate model for spatio-temporal problems. Under our approach the time trend for each geographic unit is modeled parametrically, projecting it on a preset orthogonal basis of functions (the contrasts in the smoothed ANOVA nomenclature), while the coefficients of these projections are considered to be spatially dependent random effects. Despite the parametric temporal nature of our proposal, we show with both simulated and real datasets that it may be as flexible as other spatio-temporal smoothing models proposed in the literature and may model spatio-temporal data with several sources of variability. |
| Databáze: | OpenAIRE |
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