Detalle Publicación

ARTÍCULO
Robust integral compounding criteria for trend and correlation structures
Autores: Stehlik, M.; López Fidalgo, Jesús Fernando; Casero-Alonso, V.; Bukina, E.
Título de la revista: STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
ISSN: 1436-3240
Volumen: 29
Número: 2
Páginas: 379 - 395
Fecha de publicación: 2015
Resumen:
Optimal design is a crucial issue in Environmental measurement with typical time-space correlated observations. A modified Arrhenius model with a particular correlation structure will be applied to the methane removal in the atmosphere, a very important environmental issue at this moment. We introduce a class of integrated compound criteria for obtaining robust designs. In particular, the paper provides an insight into the relationship of a compound D-optimality criterion for both the trend and covariance parameters, and the Integrated Mean Squared Prediction Error (IMSPE) criterion. In general, if there are two or more approaches of a given problem, e.g. two rival models or two different parts of a model, an integral relationship may be constructed with the aim of finding a suitable compromise between them. The Fisher information matrix (FIM) will be used in both cases. Then the integral compound criterion with respect to a density from a given parametric family of distributions is optimized. We also discuss some general conditions around the behavior of the introduced approach for comparing the FIMs and provide computing methods.