Post-breakup unwanted pursuit: a refined analysis of the role of romantic relationship characteristics

This study re-examined the role of romantic relationship characteristics in unwanted pursuit behavior (UPB) perpetration. Relationship characteristics were investigated accounting for the role of breakup characteristics using data from 396 divorced adults and advanced count regressions. The main effects of former relationship characteristics (except conflict) did not contribute explained variance to the frequency of UPBs when controlling for significant breakup characteristics (initiator status and post-breakup negative affect). However, moderator analyses revealed significant effects of relationship satisfaction, alternatives, investments, and anxious attachment in interaction with initiator status and of relationship alternatives in interaction with post-breakup negative affect. These findings illustrate that the association between relationship characteristics and UPB perpetration is more complex than previously thought and are theoretically and clinically valuable

Detecting Unspecified Structure in Low-Count Images

Unexpected structure in images of astronomical sources often presents itself upon visual inspection of the image, but such apparent structure may either correspond to true features in the source or be due to noise in the data. This paper presents a method for testing whether inferred structure in an image with Poisson noise represents a significant departure from a baseline (null) model of the image. To infer image structure, we conduct a Bayesian analysis of a full model that uses a multiscale component to allow flexible departures from the posited null model. As a test statistic, we use a tail probability of the posterior distribution under the full model. This choice of test statistic allows us to estimate a computationally efficient upper bound on a p-value that enables us to draw strong conclusions even when there are limited computational resources that can be devoted to simulations under the null model. We demonstrate the statistical performance of our method on simulated images. Applying our method to an X-ray image of the quasar 0730+257, we find significant evidence against the null model of a single point source and uniform background, lending support to the claim of an X-ray jet

Latent Gaussian Count Time Series Modeling

This paper develops theory and methods for the copula modeling of stationary count time series. The techniques use a latent Gaussian process and a distributional transformation to construct stationary series with very flexible correlation features that can have any pre-specified marginal distribution, including the classical Poisson, generalized Poisson, negative binomial, and binomial count structures. A Gaussian pseudo-likelihood estimation paradigm, based only on the mean and autocovariance function of the count series, is developed via some new Hermite expansions. Particle filtering methods are studied to approximate the true likelihood of the count series. Here, connections to hidden Markov models and other copula likelihood approximations are made. The efficacy of the approach is demonstrated and the methods are used to analyze a count series containing the annual number of no-hitter baseball games pitched in major league baseball since 1893

The temporal pattern and the overall effect of ozone exposure on pediatric respiratory morbidity

Up to now no study has investigated the temporal pattern of children’s respiratory morbidity due to ozone. In the present study, we investigate the temporal pattern and the general effect of ozone exposure on children and adolescents’ respiratory morbidity using data from a particularly well suited area in southern Europe to assess the health effects of ozone. The effects of ozone are estimated using the recently developed distributed lag non-linear models allowing for a relatively long timescale, while controlling for weather effects, a range of other air pollutants, and long and short term patterns. The public health significance of the estimated effects is higher than has been previously reported in the literature, providing evidence contrary to the conjecture that the ozone-morbidity association is mainly due to short-term harvesting. In fact, our data analysis reveals that the effects of ozone at medium and long timescales (harvesting-resistant) are substantially larger than the effects at shorter timescales (harvesting-prone), a finding that is consistent.non-linear models; distributed lag; delayed effects; public health; respiratory morbidity; children; ozone.