Adaptive wavelet estimation of a function in an indirect regression model

We consider a nonparametric regression model where m noise-perturbed functions f ₁,…,f _m are randomly observed. For a fixed ν∈{1,…,m}, we want to estimate f _ν from the observations. To reach this goal, we develop an adaptive wavelet estimator based on a hard thresholding rule. Adopting the mean integrated squared error over Besov balls, we prove that it attains a sharp rate of convergence. Simulation results are reported to support our theoretical findings.     

On sequential Monte Carlo sampling methods for Bayesian filtering

In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed. We show in particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature; these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.     

Robust online scale estimation in time series: A model-free approach

This paper presents variance extraction procedures for univariate time series. The volatility of a times series is monitored allowing for non-linearities, jumps and outliers in the level. The volatility is measured using the height of triangles formed by consecutive observations of the time series. This idea was proposed by Rousseeuw and Hubert [1996. Regression-free and robust estimation of scale for bivariate data. Comput. Statist. Data Anal. 21, 67–85] in the bivariate setting. This paper extends their procedure to apply for online scale estimation in time series analysis. The statistical properties of the new methods are derived and finite sample properties are given. A financial and a medical application illustrate the use of the procedures.     

Risk Measure Inference

We propose a bootstrap-based test of the null hypothesis of equality of two firms’ conditional risk measures (RMs) at a single point in time. The test can be applied to a wide class of conditional risk measures issued from parametric or semiparametric models. Our iterative testing procedure produces a grouped ranking of the RMs, which has direct application for systemic risk analysis. Firms within a group are statistically indistinguishable from each other, but significantly more risky than the firms belonging to lower ranked groups. A Monte Carlo simulation demonstrates that our test has good size and power properties. We apply the procedure to a sample of 94 U.S. financial institutions using ΔCoVaR, MES, and %SRISK. We find that for some periods and RMs, we cannot statistically distinguish the 40 most risky firms due to estimation uncertainty.     

Contrast Estimation for Parametric Stationary Determinantal Point Processes

We study minimum contrast estimation for parametric stationary determinantal point processes. These processes form a useful class of models for repulsive (or regular, or inhibitive) point patterns and are already applied in numerous statistical applications. Our main focus is on minimum contrast methods based on the Ripley's K‐function or on the pair correlation function. Strong consistency and asymptotic normality of theses procedures are proved under general conditions that only concern the existence of the process and its regularity with respect to the parameters. A key ingredient of the proofs is the recently established Brillinger mixing property of stationary determinantal point processes. This work may be viewed as a complement to the study of Y. Guan and M. Sherman who establish the same kind of asymptotic properties for a large class of Cox processes, which in turn are models for clustering (or aggregation).     

The cosine geometric distribution with count data modeling

In this paper, a new two-parameter discrete distribution is introduced. It belongs to the family of the weighted geometric distribution (GD), with the feature of using a particular trigonometric weight. This configuration adds an oscillating property to the former GD which can be helpful in analyzing the data with over-dispersion, as developed in this study. First, we present the basic statistical properties of the new distribution, including the cumulative distribution function, hazard rate function and moment generating function. Estimation of the related model parameters is investigated using the maximum likelihood method. A simulation study is performed to illustrate the convergence of the estimators. Applications to two practical datasets are given to show that the new model performs at least as well as some competitors.     

Perception of Prosodic Boundary Correlates by Newborn Infants

French newborn infants were shown to perceive acoustic correlates of phonological phrase boundaries in Spanish, with stress‐controlled stimuli. Access to phonological phrase boundaries may facilitate the acquisition of a lexicon, as well as some aspects of phonology and even syntax.     

Do Beveridgian pension systems increase growth?

In this paper, we explain why the structure of pension systems has an impact on the growth rate of an economy. Using a capital accumulation model, we show that the more a pension system is Beveridgian, the higher the growth rate of the economy is.     

Construction d'un problème public autour du dopage et reconnaissance d'une spécialité médicale

The formation of a professional specialty — sports medicine — is described with emphasis on how drug abuse has become a public issue. This notion's itinerary is traced between 1955 and 1999 so as to show how doctors with different profiles and activities successively raised the issue of “doping”. The objectives of medicine, as it was being applied to sports, gradually changed. At the start, the intention was to cure, a view that celebrated the virtues of practicing a sport and it condemned using drugs. A new field of medical competence was opened with the “biological preparation of performances”, which, though presented as an alternative to using drugs, blurred the boundaries with doping. Medical positions became polarized: on the one side, a science of training took shape around the physiology of physical efforts, which made it possible to intensify activities while optimizing them thanks to rest periods; and on the other side, clinicians who, in closer contact with the everyday life of players, both understood the requirements ensuing from a continuous renewal of performances and tended to favor taking “products” for “curative” purposes. Sports medicine was legitimated as a medical specialty on two grounds: the one, obvious, sets doping at odds with health; and the other, aberrant from the viewpoint of health but nonetheless accepted, associates intensive sports with health.     

Le contrôle du travail par les ouvriers : analyses à partir d'observations participantes

The sociology and anthropology of labor have long drawn attention to the ways employees exercise control over the work process, including in contexts where strong orders are given. The control of work is, in fact, an aspect of how participation and involvement in a collective organization are managed. Workers try to manage their participation (always collective but to varying degrees) in a firm in order to make work a gratifying or at least bearable experience. This involves at least three sorts of interventions linked to practical interests: managing relations with colleagues; managing the execution of tasks and activities; and managing relations with the staff. Focusing on the actor's viewpoint and objectives, this research based on participant observation examines how workers try to act so as to facilitate their activities in the short or middle run. Their efforts sometimes correspond to what the hierarchy expects but, at other times, to a form of rebellion.