Correlation and variable importance in random forests

This paper is about variable selection with the random forests algorithm in presence of correlated predictors. In high-dimensional regression or classification frameworks, variable selection is a difficult task, that becomes even more challenging in the presence of highly correlated predictors. Firstly we provide a theoretical study of the permutation importance measure for an additive regression model. This allows us to describe how the correlation between predictors impacts the permutation importance. Our results motivate the use of the recursive feature elimination (RFE) algorithm for variable selection in this context. This algorithm recursively eliminates the variables using permutation importance measure as a ranking criterion. Next various simulation experiments illustrate the efficiency of the RFE algorithm for selecting a small number of variables together with a good prediction error. Finally, this selection algorithm is tested on the Landsat Satellite data from the UCI Machine Learning Repository.     

Trends in Mortality Decrease and Economic Growth

The vast literature on extrapolative stochastic mortality models focuses mainly on the extrapolation of past mortality trends and summarizes the trends by one or more latent factors. However, the interpretation of these trends is typically not very clear. On the other hand, explanation methods are trying to link mortality dynamics with observable factors. This serves as an intermediate step between the two methods. We perform a comprehensive analysis on the relationship between the latent trend in mortality dynamics and the trend in economic growth represented by gross domestic product (GDP). Subsequently, the Lee-Carter framework is extended through the introduction of GDP as an additional factor next to the latent factor, which provides a better fit and better interpretable forecasts.     

Risk Assessment for Hospital-Acquired Diseases: A Risk-Theory Approach

We introduce a new approach to hospital-acquired disease risk assessment from public health databases. In a spirit similar to actuarial risk theory, we define an adjustment coefficient that can quantify the risk associated with a hospital department, allowing comparisons of similar departments. The adjustment coefficient characterizes the tail of the distribution of the total patient length of stay in a department before the first disease event occurs. We show that this coefficient is the solution of a Lundberg-like equation, and we provide a nonparametric estimation procedure for this measure, based on a Cramér-Lundberg approximation for the tail of the distribution. Using simulations, we provide evidence of the robustness of the approximation to various individual risk models. In addition, we illustrate the relevance of this approach by evaluating the risk associated with a standard patient safety indicator in 20 hospitals of southeastern France.     

Entry and Exit in OTC Derivatives Markets

We develop a parsimonious model to study the equilibrium and socially optimal decisions of banks to enter, trade in, and possibly exit, an OTC market. Although we endow all banks with the same trading technology, banks' optimal entry and trading decisions endogenously lead to a realistic market structure composed of dealers and customers with distinct trading patterns. We decompose banks' entry incentives into incentives to hedge risk and incentives to make intermediation profits. We show that dealer banks enter more than is socially optimal. In the face of large negative shocks, they may also exit more than is socially optimal when markets are not perfectly resilient.     

Time‐change models for asymmetric processes

Many records in environmental sciences exhibit asymmetric trajectories. The physical mechanisms behind these records may lead for example to sample paths with different characteristics at high and low levels (up–down asymmetries) or in the ascending and descending phases leading to time irreversibility (front–back asymmetries). Such features are important for many applications, and there is a need for simple and tractable models that can reproduce them. In this paper, we explore original time‐change models where the clock is a stochastic process that depends on the observed trajectory. The ergodicity of the proposed model is established under general conditions, and this result is used to develop nonparametric estimation procedures based on the joint distribution of the process and its derivative. The methodology is illustrated on meteorological and oceanographic data sets. We show that, combined with a marginal transformation, the proposed methodology is able to reproduce important characteristics of the data set such as marginal distributions, up‐crossing intensity, and up–down and front–back asymmetries.     

欧洲青年白皮书由来及对青年的影响

本文译自《二十一世纪论坛》2007年第8期,是StefanBecsky博士邀请作者撰写一篇有关白皮书对欧洲青年影响的文章。作者审视与回顾了过去十年来欧洲青年政策发展变化的历程,对未来十年青年工作具有指导意义。作者曾积极参与了有关青年白皮书项目的工作,作者希望读者们通过阅读,获得第一手资料并分享作者个人的经验。     

Civil Society Meta-organizations and Legitimating Processes: the Case of the Addiction Field in France

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - To cope with the new challenges inherent to their political role, civil society organizations must convince their...     

Japanese Children’s Knowledge of the Facial Components of Basic Emotions

While numerous studies have investigated children’s recognition of facial emotional expressions, little evidence has been gathered concerning their explicit knowledge of the components included in such expressions. Thus, we investigated children’s knowledge of the facial components involved in the expressions of happiness, sadness, anger, and surprise. Four- and 5-year-old Japanese children were presented with the blank face of a young character, and asked to select facial components in order to depict the emotions he felt. Children’s overall performance in the task increased as a function of age, and was above chance level for each emotion in both age groups. Children were likely to select the Cheek raiser and Lip corner puller to depict happiness, the Inner brow raiser, Brow lowerer, and Lid droop to depict sadness, the Brow lowerer and Upper lid raiser to depict anger, and the Upper lid raiser and Jaw drop to depict surprise. Furthermore, older children demonstrated a better knowledge of the involvement of the Upper lid raiser in surprise expressions.     

Invisible computer for collaborative design: evaluation of a multimodal sketch-based environment

In the areas of design, especially in architectural design, collaboration has become an important challenge. The specialization of skills increase, work teams are more and more extensive and the geographic distance between them increases too. The economic and ecological stakes related to remote collaboration are an evidence. This context involves the need to support most efficiently possible remote working meetings. We present the Distributed Collaborative Digital Studio (DSDC), a tool designed to recreate, in distant situations, the context of copresence meetings. This shared environment is created in the "invisible computer" approach [11]. The idea is that the tool should disappear from user's consciousness. Indeed, creative design activities require some fluidity in their process. Therefore, any involuntary interruption created by the system can potentially brake creativity. In this perspective, we investigate specifically the "invisibility" of our environment. To do this, we propose a framework for the operationalization of the concept and a methodology to test the system invisibility. This methodology was applied through a case study consisting of a corpus of 12 hours of remote collaborative design sessions with the DSDC. We highlight the learning effects while using our system, conclude on its effectiveness and discuss our methodology.