“Responsiveness of mature oak trees (Quercus robur L.) to soil water dynamics and meteorological constraints in urban environments”

Urban Ecosystems - Urban trees contribute to the regulation of microclimates of cities through transpirational cooling. The main environmental factors determining transpiration are evaporative...     

On probability matching priors

First‐order probability matching priors are priors for which Bayesian and frequentist inference, in the form of posterior quantiles, or confidence intervals, agree to a second order of approximation. The authors show that the matching priors developed by Peers (1965) and Tibshirani (1989) are readily and uniquely implemented in a third‐order approximation to the posterior marginal density. The authors further show how strong orthogonality of parameters simplifies the arguments. Several examples illustrate their results.     

Evidence of Convergence Clubs Using Mixture Models

Cross-country economic convergence has been increasingly investigated by finite mixture models. Multiple components in a mixture reflect groups of countries that converge locally. Testing for the number of components is crucial for detecting “convergence clubs.” To assess the number of components of the mixture, we propose a sequential procedure that compares the shape of the hypothesized mixture distribution with the true unknown density, consistently estimated through a kernel estimator. The novelty of our approach is its capability to select the number of components along with a satisfactory fitting of the model. Simulation studies and an empirical application to per capita income distribution across countries testify for the good performance of our approach. A three-clubs convergence seems to emerge.     

Some Remarks on Latent Variable Models in Categorical Data Analysis

We present an overview of some important and/or interesting contributions to the latent variable literature for the analysis of multivariate categorical responses, beginning with Lazarsfeld's introduction of latent class models. There is by now an enormous literature on latent variable models for categorical responses, especially in the context of including random effects in generalized linear mixed models, so this is necessarily a highly selective overview. Due to space considerations, we summarize the main ideas, suppressing details. As part of our presentation, we raise a couple of questions that may suggest future research work.     

Predictive control of posterior robustness for sample size choice in a Bernoulli model

In this article we consider the sample size determination problem in the context of robust Bayesian parameter estimation of the Bernoulli model. Following a robust approach, we consider classes of conjugate Beta prior distributions for the unknown parameter. We assume that inference is robust if posterior quantities of interest (such as point estimates and limits of credible intervals) do not change too much as the prior varies in the selected classes of priors. For the sample size problem, we consider criteria based on predictive distributions of lower bound, upper bound and range of the posterior quantity of interest. The sample size is selected so that, before observing the data, one is confident to observe a small value for the posterior range and, depending on design goals, a large (small) value of the lower (upper) bound of the quantity of interest. We also discuss relationships with and comparison to non robust and non informative Bayesian methods.     

Various Approaches for Predicting Land Cover in Mountain Areas

Using former maps, geographers intend to study the evolution of the land cover in order to have a prospective approach on the future landscape; predictions of the future land cover, by the use of older maps and environmental variables, are usually done through the GIS (Geographic Information System). We propose here to confront this classical geographical approach with statistical approaches: a linear parametric model (polychotomous regression modeling) and a nonparametric one (multilayer perceptron). These methodologies have been tested on two real areas on which the land cover is known at various dates; this allows us to emphasize the benefit of these two statistical approaches compared to GIS and to discuss the way GIS could be improved by the use of statistical models.     

The Accessibility of Public Spaces for People with Dementia: a new priority for the 'open city'

The social model of disability de-medicalises disability and politicises it as an issue of universal rights. However, the rights of people with dementia have been less strongly advocated than those of people with physical disabilities. This is particularly the case with environmental planning and design. The needs of people with dementia are now informing the design of residential homes and day centres, but the issue of accessibility to public spaces and amenities has been almost completely neglected. Many outdoor environments such as shopping centres or parks may be inhospitable for people with dementia because they are disorientating, difficult to interpret and navigate, threatening or distressing. The article reviews the literature on indoor design for dementia, reports on research investigating the accessibility of outdoor environments, and describes a new approach using virtual reality technology to enable people with dementia to identify and test outdoor design and planning improvements themselves.     

In Their Own Words: Challenges Facing Youth Aging Out of Foster Care

Since 1999 there has been a renewed effort addressing the challenges youth face exiting foster care in adolescence, yet outcomes for most youth are still indicating heartbreaking results and it is still not clear what more is needed. Presented is a study addressing what is needed for successful transition. Three major themes emerged; youth focused practice, need for collaboration and better communication with youth, and unmet needs and permanent connections.