Gamma-based clustering via ordered means with application to gene-expression analysis

Discrete mixture models provide a well-known basis for effective clustering algorithms, although technical challenges have limited their scope. In the context of gene-expression data analysis, a model is presented that mixes over a finite catalog of structures, each one representing equality and inequality constraints among latent expected values. Computations depend on the probability that independent gamma-distributed variables attain each of their possible orderings. Each ordering event is equivalent to an event in independent negative-binomial random variables, and this finding guides a dynamic-programming calculation. The structuring of mixture-model components according to constraints among latent means leads to strict concavity of the mixture log likelihood. In addition to its beneficial numerical properties, the clustering method shows promising results in an empirical study.Comment: Published in at http://dx.doi.org/10.1214/10-AOS805 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Correspondence between HBT radii and the emission zone in non-central heavy ion collisions

In non-central collisions between ultra-relativistic heavy ions, the freeze-out distribution is anisotropic, and its major longitudinal axis may be tilted away from the beam direction. The shape and orientation of this distribution are particularly interesting, as they provide a snapshot of the evolving source and reflect the space-time aspect of anisotropic flow. Experimentally, this information is extracted by measuring pion HBT radii as a function of angle with respect to the reaction plane. Existing formulae relating the oscillations of the radii and the freezeout anisotropy are in principle only valid for Gaussian sources with no collective flow. With a realistic transport model of the collision, which generates flow and non-Gaussian sources, we find that these formulae approximately reflect the anisotropy of the freezeout distribution.Comment: 9 pages, 8 figure

Pregnancy, prison and perinatal outcomes in New South Wales, Australia: a retrospective cohort study using linked health data

BACKGROUND Studies from the United States and the United Kingdom have found that imprisoned women are less likely to experience poorer maternal and perinatal outcomes than other disadvantaged women. This population-based study used both community controls and women with a history of incarceration as a control group, to investigate whether imprisoned pregnant women in New South Wales, Australia, have improved maternal and perinatal outcomes. METHODS Retrospective cohort study using probabilistic record linkage of routinely collected data from health and corrective services in New South Wales, Australia. Comparison of the maternal and perinatal outcomes of imprisoned pregnant women aged 18-44 years who gave birth between 2000-2006 with women who were (i) imprisoned at a time other than pregnancy, and (ii) community controls. OUTCOMES OF INTEREST onset of labour, method of birth, pre-term birth, low birthweight, Apgar score, resuscitation, neonatal hospital admission, perinatal death. RESULTS Babies born to women who were imprisoned during pregnancy were significantly more likely to be born pre-term, have low birthweight, and be admitted to hospital, compared with community controls. Pregnant prisoners did not have significantly better outcomes than other similarly disadvantaged women (those with a history of imprisonment who were not imprisoned during pregnancy). CONCLUSIONS In contrast to the published literature, we found no evidence that contact with prison health services during pregnancy was a "therapunitive" intervention. We found no association between imprisonment during pregnancy and improved perinatal outcomes for imprisoned women or their neonates. A history of imprisonment remained the strongest predictor of poor perinatal outcomes, reflecting the relative health disadvantage experienced by this population of women.This work was undertaken with funding from the National Health and Medical Research Council of Australia. Project Grant ID 457515

The Effect Demographics Have On The Demand For Orange Juice

This paper investigates how the demand for orange juice is affected by the demographics of consumers. There are many variables in the orange juice demand equation and demographics are only one. Demographic variables are important in determining the tastes and preferences of different regions. The data that has been collected is weekly data over a two year period of time. The seemingly unrelated regression method will be used to examine the data. This project will be beneficial to orange juice advertising firms and companies that sell orange juice.Food Consumption/Nutrition/Food Safety, Marketing,