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This paper proposes a new approach to sparse-signal detection called the horseshoe estimator. We show that the horseshoe is a close cousin of the lasso in that it arises from the same class of multivariate scale mixtures of normals, but that it is almost universally superior to the double-exponential prior at handling sparsity. A theoretical framework is(More)
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BACKGROUND Measuring disease and injury burden in populations requires a composite metric that captures both premature mortality and the prevalence and severity of ill-health. The 1990 Global Burden of Disease study proposed disability-adjusted life years (DALYs) to measure disease burden. No comprehensive update of disease burden worldwide incorporating a(More)
BACKGROUND Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional(More)
We study the classic problem of choosing a prior distribution for a location parameter β = (β 1 ,. .. , βp) as p grows large. First, we study the standard " global-local shrinkage " approach, based on scale mixtures of normals. Two theorems are presented which characterize certain desirable properties of shrinkage priors for sparse problems. Next, we review(More)
This paper presents a general, fully Bayesian framework for sparse supervised-learning problems based on the horseshoe prior. The horseshoe prior is a member of the family of multivariate scale mixtures of normals, and is therefore closely related to widely used approaches for sparse Bayesian learning, including , among others, Laplacian priors (e.g. the(More)
BACKGROUND Child sexual abuse is considered a modifiable risk factor for mental disorders across the life course. However the long-term consequences of other forms of child maltreatment have not yet been systematically examined. The aim of this study was to summarise the evidence relating to the possible relationship between child physical abuse, emotional(More)
This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. The first goal of the paper is to clarify when, and how, multiplicity correction is automatic in Bayesian analysis, and contrast this multiplicity correction with the Bayesian Ockham's-razor effect. Secondly, we contrast empirical-Bayes(More)
BACKGROUND Apart from individuals with clinical psychosis, community surveys have shown that many otherwise well individuals endorse items designed to identify psychosis. The aim of this study was to characterize the demographic correlates of individuals who endorse psychosis screening items in a large general community sample. METHOD The National Survey(More)
BACKGROUND Birth cohort studies have shown that individuals who develop non-affective psychoses display subtle deviations in behaviour during childhood and adolescence. We had the opportunity to examine the widely used Child Behavior Checklist (CBCL) and the Youth Self-Report (YSR) to explore the antecedents of non-affective psychosis. METHOD Based on a(More)