Ultrastructural elliptical models

Dolby's (1976) ultrastructural model with no replications is investigated within the class of the elliptical distributions. General asymptotic results are given for the sample covariance matrix S in the presence of incidental parameters. These results are used to study the asymptotic behaviour of some estimators of the slope parameter, unifying and extending existing results in the literature. In particular, under some regularity conditions they are shown to be consistent and asymptotically normal. For the special case of the structural model, some asymptotic relative efficiencies are also reported which show that generalized least squares and the method of moment estimators can be highly inefficient under nonnormality.     

Bayesian prediction for progressively censored data from the Burr model

Received: August 14, 2000; revised version: April 23, 2001     

The Obese Smoker's Wage Penalty*

Objective. Smoking and obesity are associated with significant wage penalties when considered separately. We assess the combined effects of those behaviors. Methods. We estimate the effects of smoking and obesity on wages using multivariate regression analysis with 1979 National Longitudinal Survey of Youth data. Results. The raw data indicate that obese smokers experience large earnings penalties. However, these penalties are not found to be interactive or directly causal for most of the demographic subgroups we examine. One exception is the wage penalty associated with obesity for females, which remains significant throughout the analysis. Conclusions. In the absence of a demonstrable direct causal effect of those behaviors on wages, associated individual‐specific socioeconomic factors appear to be the driving forces behind the obese smoker wage penalty. Not included, but potentially significant, are the effects of employer and customer discrimination against obese smokers and the possible labor policy implications of such discrimination.     

A multistate approach for estimating the incidence of human immunodeficiency virus by using data from a prevalent cohort study

Summary.  Cohort studies of individuals infected with the human immunodeficiency virus (HIV) provide useful information on the past pattern of HIV diagnoses, progression of the disease and use of antiretroviral therapy. We propose a new method for using individual data from an open prevalent cohort study to estimate the incidence of HIV, by jointly modelling the HIV diagnosis, the inclusion in the cohort and the progression of the disease in a Markov model framework. The estimation procedure involves the construction of a likelihood function which takes into account the probability of observing the total number of subjects who are enrolled in the cohort and the probabilities of passage through the stages of disease for each observed subject conditionally on being included in the cohort. The estimator of the HIV infection rate is defined as the function which maximizes a penalized likelihood, and the solution of this maximization problem is approximated on a basis of cubic M -splines. The method is illustrated by using cohort data from a hospital-based surveillance system of HIV infection in Aquitaine, a region of south-western France. A simulation study is performed to study the ability of the model to reconstruct the incidence of HIV from prevalent cohort data.     

A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces

Differential Evolution (DE) is a simple genetic algorithm for numerical optimization in real parameter spaces. In a statistical context one would not just want the optimum but also its uncertainty. The uncertainty distribution can be obtained by a Bayesian analysis (after specifying prior and likelihood) using Markov Chain Monte Carlo (MCMC) simulation. This paper integrates the essential ideas of DE and MCMC, resulting in Differential Evolution Markov Chain (DE-MC). DE-MC is a population MCMC algorithm, in which multiple chains are run in parallel. DE-MC solves an important problem in MCMC, namely that of choosing an appropriate scale and orientation for the jumping distribution. In DE-MC the jumps are simply a fixed multiple of the differences of two random parameter vectors that are currently in the population. The selection process of DE-MC works via the usual Metropolis ratio which defines the probability with which a proposal is accepted. In tests with known uncertainty distributions, the efficiency of DE-MC with respect to random walk Metropolis with optimal multivariate Normal jumps ranged from 68% for small population sizes to 100% for large population sizes and even to 500% for the 97.5% point of a variable from a 50-dimensional Student distribution. Two Bayesian examples illustrate the potential of DE-MC in practice. DE-MC is shown to facilitate multidimensional updates in a multi-chain “Metropolis-within-Gibbs” sampling approach. The advantage of DE-MC over conventional MCMC are simplicity, speed of calculation and convergence, even for nearly collinear parameters and multimodal densities.     

Emerging trends in US retailing

This article examines the trends shaping the retail environment as we enter the next century. A modified delphi approach was used to access managerial perceptions of the changing retail landscape. Changes in consumer markets, price and branding strategy, store formats, retail institutions and applications of technology were derived from the analysis. From this, a series of managerial considerations are proposed to focus retail managers on developing new strategies to position themselves effectively in the new global marketplace.     

Theory in Ethno-Logic*

Because thought processes underlie all human action and can distinguish one culture from another, the social sciences must face the problem of determining how people think. Reasoning can be viewed as abstract and not connected to any particular human activity, as it is in philosophical logic, or it can be seen as a process in a particular linguistic, social and cultural setting, as it is in ethno-logic. Recently anthropologists, developmental psychologists and other scholars working under the general rubric of cognitive science have studied issues in ethno-logic but these studies are flawed because the researchers accepted philosophical logic as the norm under which they judged the actions of their subjects. Good theory in ethno-logic can only come from study which describes thought processes from the natives point of view. One such theory states that conclusions are logically established on the semantic structure of the argument. This theory accounts for both universal and culture specific aspects of reasoning, is testable, opens new areas of research and provides researchers with a firmly grounded method for using meaning to account for behavior.