The multivariate alpha-power model

The main object of this paper is to propose a multivariate extension to the alpha-power model which is an alternative to the multivariate skew-normal model (Arellano-Valle and Azzalini, 2008). It also extends the power-normal model discussed in Gupta and Gupta (2008) by making it more flexible. Inference is dealt with by using the likelihood approach and a pseudo-likelihood approach based on conditional distributions which, although slightly less efficient, is simpler to implement. An application to a real data set is used to demonstrate the usefulness of the extension.     

Bayesian outlier testing using the predictive distribution for a linear model op constant intraclass form

The problem of testing suspected outliers from a linear model with constant intraclass correlation is considered from a Bayesian viewpoint. The main objective of this paper is to develop an outlier test procedure based on the predictive distribution of suspected outlier observations given a set of existing inlier observations. The test procedure is easily performed with the usual F and t distributions.     

Re-instating the vague

From medicine and military warfare to the practices of modern management, we have come to pursue the ideal of precision in order to generate the knowledge necessary to organise our social, cultural and economic lives. Underpinning this valorisation of the ideal of precision is a repulsion for its opposite –vagueness– which is habitually treated as a synonym for chaos, uncertainty and uselessness. Yet vagueness, understood here as a condition of radical uncertainty or open possibility, is inescapably imbricated in the triumphs of precision. This paper challenges this neglect by arguing that, once stripped of its pejorative connotations, vagueness can be understood as the silent but often salient partner in a marriage of opposites. Tracing the conceptual pairing of these contrasting terms, the paper goes on to suggest that instead of prising them apart we need to recognise their mutual reciprocity. By holding vagueness and precision in dynamic tension, it is suggested, we can develop a critical exploration of contemporary thinking in public policy formulation with its predilection for ‘joined‐up thinking’ and a general ‘blurring of boundaries’.     

Approximating probability density functions in hybrid Bayesian networks with mixtures of truncated exponentials

Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization and Monte Carlo methods for solving hybrid Bayesian networks. Any probability density function (PDF) can be approximated by an MTE potential, which can always be marginalized in closed form. This allows propagation to be done exactly using the Shenoy-Shafer architecture for computing marginals, with no restrictions on the construction of a join tree. This paper presents MTE potentials that approximate standard PDF’s and applications of these potentials for solving inference problems in hybrid Bayesian networks. These approximations will extend the types of inference problems that can be modelled with Bayesian networks, as demonstrated using three examples.     

Fathers-The Secondary Partners: Professional Perceptions and Fathers' Reflections

SUMMARY. The following is an account of a research project exploring the recollections of seven fathers at the time of the birth of their children with Down's Syndrome. It discusses the disclosure of diagnosis and subsequent contacts the fathers made both professionally and socially during the period following both in the hospital and at home. This is combined with the personal recollections of one father, not part of the original study, whose child was born with special needs. The implications for both professional practice and fathers are highlighted. Whilst there is an acknowledgement that the project was small scale, the conclusions will raise challenging issues for further discussion both among professionals and individual members of families.     

The spatial structure of epidemic emergence: geographical aspects of poliomyelitis in north-eastern USA, July-October 1916

Summary.  The great epidemic of poliomyelitis which swept New York City and surrounding territory in the summer of 1916 eclipsed all previous global experience of the disease. We draw on epidemiological information that is included in the seminal US Public Health Bulletin 91, 'Epidemiologic studies of poliomyelitis in New York City and the northeastern United States during the year 1916' (Washington DC, 1918), to re-examine the spatial structure of the epidemic. For the main phase of transmission of the epidemic, July–October 1916, it is shown that the maximum concentration of activity of poliomyelitis occurred within a 128-km radius of New York City. Although the integrity of the poliomyelitis cluster was maintained up to approximately 500 km from the metropolitan focus, the level and rate of propagation of disease declined with distance from the origin of the epidemic. Finally, it is shown that the geographical transmission of the epidemic in north-eastern USA probably followed a process of mixed contagious–hierarchical diffusion.