On Typical Compact Convex Sets in Hilbert Spaces

Let E be an infinite dimensional separable space and for e ∈ E and X a nonempty compact convex subset of E, let qX(e) be the metric antiprojection of e on X. Let n ≥ 2 be an arbitrary integer. It is shown that for a typical (in the sence of the Baire category) compact convex set X ⊂ E the metric antiprojection qX(e) has cardinality at least n for every e in a dense subset of E

Bayesian nonparametric estimation and consistency of mixed multinomial logit choice models

This paper develops nonparametric estimation for discrete choice models based on the mixed multinomial logit (MMNL) model. It has been shown that MMNL models encompass all discrete choice models derived under the assumption of random utility maximization, subject to the identification of an unknown distribution $G$. Noting the mixture model description of the MMNL, we employ a Bayesian nonparametric approach, using nonparametric priors on the unknown mixing distribution $G$, to estimate choice probabilities. We provide an important theoretical support for the use of the proposed methodology by investigating consistency of the posterior distribution for a general nonparametric prior on the mixing distribution. Consistency is defined according to an $L_1$-type distance on the space of choice probabilities and is achieved by extending to a regression model framework a recent approach to strong consistency based on the summability of square roots of prior probabilities. Moving to estimation, slightly different techniques for non-panel and panel data models are discussed. For practical implementation, we describe efficient and relatively easy-to-use blocked Gibbs sampling procedures. These procedures are based on approximations of the random probability measure by classes of finite stick-breaking processes. A simulation study is also performed to investigate the performance of the proposed methods.Comment: Published in at http://dx.doi.org/10.3150/09-BEJ233 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Bayesian Nonparametric Estimation and Consistency of Mixed Multinomial Logit Choice Models

This paper develops nonparametric estimation for discrete choice models based on the Mixed Multinomial Logit (MMNL) model. It has been shown that MMNL models encompass all discrete choice models derived under the assumption of random utility maximization, subject to the identification of an unknown distribution G. Noting the mixture model description of the MMNL, we employ a Bayesian nonparametric approach, using nonparametric priors on the unknown mixing distribution G, to estimate the unknown choice probabilities. Theoretical support for the use of the proposed methodology is provided by establishing strong consistency of a general nonparametric prior on G under simple sufficient conditions. Consistency is defined according to a L1-type distance on the space of choice probabilities and is achieved by extending to a regression model framework a recent approach to strong consistency based on the summability of square roots of prior probabilities. Moving to estimation, slightly different techniques for non-panel and panel data models are discussed. For practical implementation, we describe efficient and relatively easy to use blocked Gibbs sampling procedures. A simulation study is also performed to illustrate the proposed methods and the exibility they achieve with respect to parametric Gaussian MMNL models.Bayesian consistency, Bayesian nonparametrics, Blocked Gibbs sampler, Discrete choice models, Mixed Multinomial Logit, Random probability measures, Stick-breaking priors

Are the school prevention programmes - aimed at de-normalizing smoking among youths - beneficial in the long term? An example from the Smoke Free Class Competition in Italy

Tobacco smoking by young people is of great concern because it usually leads to regular smoking, nicotine addiction and quitting difficulties. Young people "hooked" by tobacco maintain the profits of the tobacco industry by replacing smokers who quit or die. If new generations could be tobacco-free, as supported by tobacco endgame strategies, the tobacco epidemic could end within decades. Smoking prevention programmes for teens are offered by schools with the aim to prevent or delay smoking onset. Among these, the Smoke Free Class Competition (SFC) was widely implemented in Europe. Its effectiveness yielded conflicting results, but it was only evaluated at short/medium term (6 - 18 months). The aim of this study is to evaluate its effectiveness after a longer follow-up (3 to 5 years) in order to allow enough time for the maturing of the students and the internalization of the experience and its contents. Fifteen classes were randomly sampled from two Italian high schools of Bologna province that regularly offered the SFC to first year students; 382 students (174 participating in the SFC and 208 controls) were retrospectively followed-up and provided their "smoking histories". At the end of their last year of school (after 5 years from the SFC), the percentage of students who stated that they were regular smokers was lower among the SFC students than in controls: 13.5% vs 32.9% (p=0.03). From the students' "smoking histories", statistically significant protective ORs were observed for SFC students at the end of 1st and 5th year: 0.42 (95% CI 0.19-0.93) and 0.32 (95% CI 0.11-0.91) respectively. Absence of smokers in the family was also a strongly statistically significant factor associated with being a non-smoker student. These results suggest that SFC may have a positive impact on lowering the prevalence of smoking in the long term (5 years)

Air temperature variability over three glaciers in the Ortles-Cevedale (Italian Alps): Effects of glacier fragmentation, comparison of calculation methods, and impacts on mass balance modeling

Glacier mass balance models rely on accurate spatial calculation of input data, in particular air temperature. Lower temperatures (the so-called glacier cooling effect), and lower temperature variability (the so-called glacier damping effect) generally occur over glaciers, compared to ambient conditions. These effects, which depend on the geometric characteristics of glaciers and display a high spatial and temporal variability, have been mostly investigated on medium- to large-size glaciers so far, while observations on smaller ice bodies are scarce. Using a dataset from 8 on-glacier and 4 off-glacier weather stations, collected in summer 2010 and 2011, we analyzed the air temperature distribution variability and wind regime over three different glaciers in the Ortles-Cevedale. The magnitude of the cooling effect and the occurrence of katabatic boundary layer (KBL) processes showed remarkable differences among the three ice bodies, highlighting suggesting the likely existence of important reinforcing mechanisms during glacier decay and disintegration. None of the methods proposed in the literature for calculating on-glacier temperature from off-glacier data fully reproduced our observations. Among them, the more physically-based procedure of Greuell and B\uf6hm [1998] provided the best overall results where the KBL prevail, but it was not effective elsewhere (i.e. on smaller ice bodies and close to the glacier margins). The accuracy of air temperature estimations strongly impacted the results from a mass balance model which was applied to the three investigated glaciers. Most importantly, even small temperature deviations caused distortions in parameter calibration, thus compromising the model generalizability

On the inferential implications of decreasing weight structures in mixture models

Bayesian estimation of nonparametric mixture models strongly relies on available representations of discrete random probability measures. In particular, the order of the mixing weights plays an important role for the identifiability of component-specific parameters which, in turn, affects the convergence properties of posterior samplers. The geometric process mixture model provides a simple alternative to models based on the Dirichlet process that effectively addresses these issues. However, the rate of decay of the mixing weights for this model may be too fast for modeling data with a large number of components. The need for different decay rates arises. Some variants of the geometric process featuring different decay behaviors, while preserving the decreasing structure, are presented and investigated. An asymptotic characterization of the number of distinct values in a sample from the corresponding mixing measure is also given, highlighting the inferential implications of different prior specifications. The analysis is completed by a simulation study in the context of density estimation. It shows that by controlling the decaying rate, the mixture model is able to capture data with a large number of components

A New Strategy for Treatment of a Congenital Arteriovenous Fistula of the Neck. Case Report

AbstractCongenital arteriovenous fistulas (AVF) without associated vascular malformations are uncommon. Only a very few cases of AVF have been reported in the neck. We describe our findings in a patient with AVF treated by a combined vascular and endovascular approach