On the Validity of the Bootstrap in Non‐Parametric Functional Regression

Abstract. We consider the functional non‐parametric regression model Y= r( χ )+?, where the response Y is univariate, χ is a functional covariate (i.e. valued in some infinite‐dimensional space), and the error ? satisfies E(? | χ ) = 0. For this model, the pointwise asymptotic normality of a kernel estimator of r (·) has been proved in the literature. To use this result for building pointwise confidence intervals for r (·), the asymptotic variance and bias of need to be estimated. However, the functional covariate setting makes this task very hard. To circumvent the estimation of these quantities, we propose to use a bootstrap procedure to approximate the distribution of . Both a naive and a wild bootstrap procedure are studied, and their asymptotic validity is proved. The obtained consistency results are discussed from a practical point of view via a simulation study. Finally, the wild bootstrap procedure is applied to a food industry quality problem to compute pointwise confidence intervals.     

Takacs–Fiksel Method for Stationary Marked Gibbs Point Processes

Abstract. This article studies a method to estimate the parameters governing the distribution of a stationary marked Gibbs point process. This procedure, known as the Takacs–Fiksel method, is based on the estimation of the left and right hand sides of the Georgii–Nguyen–Zessin formula and leads to a family of estimators due to the possible choices of test functions. We propose several examples illustrating the interest and flexibility of this procedure. We also provide sufficient conditions based on the model and the test functions to derive asymptotic properties (consistency and asymptotic normality) of the resulting estimator. The different assumptions are discussed for exponential family models and for a large class of test functions. A short simulation study is proposed to assess the correctness of the methodology and the asymptotic results.     

Engineering education on production management. Different levels and degrees in five European countries: a comparison

The paper summarizes the results of the work-session ‘Education on Production Management’, organized during the Workshop and Summer School ‘Advanced Topics in Production Systems Design and Management’, held in Varenna (Lecco, Italy), from 1–4 June 1994. The organization of studies in the production management field in Denmark, France, Germany, Italy and Norway is outlined. A comparison between them shows a range of different solutions that must be understood to reach the goal of an effective exchange of production management people throughout the European Community.     

The Dantzig Selector in Cox's Proportional Hazards Model

Abstract. The Dantzig selector (DS) is a recent approach of estimation in high‐dimensional linear regression models with a large number of explanatory variables and a relatively small number of observations. As in the least absolute shrinkage and selection operator (LASSO), this approach sets certain regression coefficients exactly to zero, thus performing variable selection. However, such a framework, contrary to the LASSO, has never been used in regression models for survival data with censoring. A key motivation of this article is to study the estimation problem for Cox's proportional hazards (PH) function regression models using a framework that extends the theory, the computational advantages and the optimal asymptotic rate properties of the DS to the class of Cox's PH under appropriate sparsity scenarios. We perform a detailed simulation study to compare our approach with other methods and illustrate it on a well‐known microarray gene expression data set for predicting survival from gene expressions.     

HAS ELECTRICITY REGULATION RESULTED IN HIGHER PRICES? AN ECONOMETRIC EVALUATION UTILIZING A CALIBRATED REGULATORY INPUT VARIABLE

The universalization of regulation has made it impossible to measure its effectiveness using traditional techniques. Researchers have used dummy variables, however, the spread of regulation has gradually eliminated the control group of unregulated firms needed for this technique. This explains why Stigler and Friedland (1962) concluded their study with 1937 data. The calibrated regulatory variable technique introduced here, on the other hand, can measure the effectiveness of regulation even when it is a universal condition. We find that electricity regulation raised prices during the period 1947–1966. A politically-motivated, naive policy designed to cross-subsidize residential users may have contributed to this failure.