A study of orientational ordering in a fluid of dipolar Gay-Berne molecules using density-functional theory

Published versio

Some examples of bayesian experiments

L'esperimento bayesiano è presentato come un'unica misura di probabilità su uno spazio prodotto. Sulla base di quattro esempi si mostra come tale struttura astratta costituisca un contesto potente ed al tempo stesso flessibile per trattare situazioni che comportano livelli di sofisticazione matematica notevolmente diversi. In particolare il modello esponenziale viene presentato in un contesto completamente bayesiano

Conditioning in dynamic models

A statistical model is generally defined through a probability on some variables conditionally on other variables and refers to some parameters of interest. Therefore, it seems natural to ask under which conditions such a model does not lose information with respect to a model describing more variables and implying more parameters. Admissibility conditions for reductions by conditioning are investigated both in one-shot and in dynamic models. By so doing, concepts of ‘exogeneity’ and of ‘non-causality’ are integrated into a general framework. This paper is essentially a non-technical introduction to the theory of reduction developed more formally in other papers. It also supplies various examples of the concepts introduced in that theory

A Note on Noncausality

In this note the relationship between alternative concepts of noncausality is analyzed using the tool of conditional independence among a-fields. (For the reader who is unfamiliar with this technique, the Appendix sketches the proofs and the basic technical apparatus, along with some basic motivations.) Furthermore, the relationship between the concepts of noncausality and transitivity is made explicit in order to facilitate, in econometric modelling, the use of results already obtained in sequential analysis

Model choice : Proceedings of the 4th Franco-Belgian meeting of statisticians

This volume contains a collection of papers which were presented at the fourth Franco-Belgian Meeting of Statisticians, held in November 24 and 25, 1983 in Belgium. The articles which are gathered together here present different approaches to the major theme of the meeting : model choice. Insofar as the choice of model does not constitute a well-defined statistical problem but rather has to do with the point of view one holds about the given information, it is not at all surprising that such a variety of ideas exists on this topic. Model choice can appear to be a hypothesis testing problem nested or not, whos asymptotical theory demands a theoretical detour by way of the contiguity notion. It can also take the form of an estimation of a discrete parameter (from a Bayesian view or not). An example would be in discriminant analysis or like a non parametric test problem. while working on chronological series, it is very common to choose between varios models depending upon the given information. This volume examines both theoretically, and trough applications, the subject of model choice