In this paper, we consider Bayesian estimation and model determination for two-way contingency tables. The analysis is based on partitioning the parameter space of a saturated log-linear model into parameter subspaces identiied by considering the natural symmetries of the data. Prior distributions may then be chosen to respect invariance restrictions required by the available prior information....

BACKGROUND Recent evidence suggests that elevated ambient temperatures may trigger preterm delivery. Since results from studies in temperate climates are inconclusive, we investigated the association between temperature and the risk of preterm birth in Flanders (Belgium). METHODS We used data on 807 835 singleton deliveries (January 1998-July 2011). We combined a quasi-Poisson model with dist...

Extensive research has demonstrated that neighbourhood ethnic diversity is negatively associated with intra-neighbourhood social capital. This study explores the role of segregation and integration in this relationship. To do so it applies three-level hierarchical linear models to two sets of data from across Great Britain and within London, and examines how segregation across the wider-communi...

Classification images and bubbles images are psychophysical tools that use stimulus noise to investigate what features people use to make perceptual decisions. Previous work has shown that classification images can be estimated using the generalized linear model (GLM), and here I show that this is true for bubbles images as well. Expressing the two approaches in terms of a single statistical mo...

A key problem in the biological sciences is to be able to reliably estimate model parameters from experimental data. This is the well-known problem of parameter identifiability. Here, methods are developed for biologists and other modelers to design optimal experiments to ensure parameter identifiability at a structural level. The main results of the paper are to provide a general methodology f...

How well do classification images characterize human observers' strategies in perceptual tasks? We show mathematically that from the classification image of a noisy linear observer, it is possible to recover the observer's absolute efficiency. If we could similarly predict human observers' performance from their classification images, this would suggest that the linear model that underlies use ...

In their paper in this issue, Grusky and Charles (1998) make a number of dubious claims about the measurement and interpretation of sex segregation. First, they incorrectly claim that only log-odds measures yield margin-free measures of segregation. Second, the estimation and testing of a limited class of log-linear models does not provide an independent test of the appropriateness of a log-odd...

Robust pole placement in a LMI region for Takagi-Sugeno (Takagi & Sugeno 1985) fuzzy models is presented. The objective is to find a set of Linear Matrix Inequalities in order to ensure that the linear models poles remain in a specified region of the complex plane, even in presence of model uncertainties. As an illustration, the obtained conditions are applied to the spacing policy control of a...

Varying-coeecient models are an extension of generalized linear models. In this case the coeecients are allowed to vary smoothly with the value of other variables. We present a "local Fisher scoring backktting" algorithm based on a weighted local likelihood approach where the components are iteratively tted. An example will illustrate the usefulness of this approach.

Generalized F tests were introduced by Michalski and Zmyślony (1996) for variance components and later (1999) for linear functions of parameters in mixed linear models. We now use generalized polar coordinates to obtain, for the second case, tests that are more powerful for selected families of alternatives.