作者：Joseph, V. Roshan; Ai, Mingyao; Wu, C. F. Jeff
作者单位：University System of Georgia; Georgia Institute of Technology; Peking University
摘要：Motivated by a Bayesian framework, we propose a new minimum aberration-type criterion for designing experiments with two- and four-level factors. The Bayesian approach helps in overcoming the ad hoc nature of effect ordering in the existing minimum aberration-type criteria. The approach is also capable of distinguishing between qualitative and quantitative factors. Numerous examples are given to demonstrate its advantages.
作者：Naveau, Philippe; Guillou, Armelle; Cooley, Daniel; Diebolt, Jean
作者单位：Universite Paris Saclay; Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); Universites de Strasbourg Etablissements Associes; Universite de Strasbourg; Colorado State University System; Colorado State University Fort Collins; Universite Paris-Est-Creteil-Val-de-Marne (UPEC); Universite Gustave-Eiffel; Centre National de la Recherche Scientifique (CNRS)
摘要：We model pairwise dependence of temporal maxima, such as annual maxima of precipitation, that have been recorded in space, either on a regular grid or at irregularly spaced locations. The construction of our estimators stems from the variogram concept. The asymptotic properties of our pairwise dependence estimators are established through properties of empirical processes. The performance of our approach is illustrated by simulations and by the treatment of a real dataset. In addition to bring...
