Reference priors in non-normal location problems

Bayesian Statistics;Statistical Distribution

Multivariate Student -t Regression Models: Pitfalls and Inference

We consider likelihood-based inference from multivariate regression models with independent Student-t errors. Some very intruiging pitfalls of both Bayesian and classical methods on the basis of point observations are uncovered. Bayesian inference may be precluded as a consequence of the coarse nature of the data. Global maximization of the likelihood function is a vacuous exercise since the likelihood function is unbounded as we tend to the boundary of the parameter space. A Bayesian analysis on the basis of set observations is proposed and illustrated by several examples.Bayesian inference;Coarse data;Continuous distribution;Maximum likelihood;Missing data;Scale mixture of Normals

Reference Priors For Non-Normal Two-Sample Problems

The reference prior algorithm (Berger and Bernardo, 1992) is applied to locationscale models with any regular sampling density. A number of two-sample problems is analyzed in this general context, extending the dierence, ratio and product of Normal means problems outside Normality, while explicitly considering possibly dierent sizes for each sample. Since the reference prior turns out to be improper in all cases, we examine existence of the resulting posterior distribution and its moments under sampling from scale mixtures of Normals. In the context of an empirical example, it is shown that a reference posterior analysis is numerically feasible and can display some sensitivity to the actual sampling distributions. This illustrates the practical importance of questioning the Normality assumption.Behrens-Fisher problem;Fieller-Creasy problem;Gibbs sampling;Jeffreys' prior;location-scale model;posterior existence;product of means;scale mixtures of normals;skewness

Multiple output production with undesirable outputs : an application to nitrogen surplus in agriculture

Many production processes yield both good outputs and undesirable ones (e.g., pollutants). In this article we develop a generalization of a stochastic frontier model that is appropriate for such technologies. We discuss efficiency analysis and, in particular, define technical and environmental efficiency in the context of our model. We develop methods for carrying out Bayesian inference and apply them to a panel data set of Dutch dairy farms, where excess nitrogen production constitutes an important environmental problem

Marginal equivalence in v-spherical models

Bayesian Statistics;Models

Statistical Modelling of Fishing Activities in the North Atlantic

This paper deals with the issue of modeling daily catches of fishing boats in the Grand Bank fishing grounds. We have data on catches per species for a number of vessels collected by the European Union in the context of the North Atlantic Fisheries Organization. Many variables can be thought to influence the amount caught: a number of ship characteristics (such as the size of the ship, the fishing technique used, the mesh size of the nets, etc.), are obvious candidates, but one can also consider the season or the actual location of the catch. In all, our database leads to 23 possible regressors, resulting in a set of 8:4£106 possible linear regression models. Prediction of future catches and posterior inference will be based on Bayesian model averaging, using a Markov Chain Monte Carlo Model Composition (MC3) approach. Particular attention is paid to the elicitation of the prior and the prediction of catch for single and aggregated observations.

Inference robustness in multivariate models with a scale parameter

We formulate a general representation of points z 2Regression Analysis;Multivariate Analysis;Statistical Distribution;Scaling;statistics

Slow light with flat or offset band edges in multi-mode fiber with two gratings

We consider mode coupling in multimode optical fibers using either two Bragg gratings or a Bragg grating and a long-period grating. We show that the magnitude of the band edge curvature can be controlled leading to a flat, quartic band-edge or to two band edges at distinct, nonequivalent $k$-values, allowing precise control of slow light propagation.Comment: 6 pages, 3 figure