Christine Thomas-Agnan

Learn More
For an open subset Ω of ℝ, an integer,m, and a positive real parameter τ, the Sobolev spacesH m (Ω) equipped with the norms: ∥u∥2=∫u(t)2dt+(1/τ2m ∫u (m)(t)2 constitute a family of reproducing kernel Hilbert spaces. When Ω is an open interval of the real line, we describe the computation of their reproducing kernels. We derive explicit formulas for these(More)
We present GeoXp, an R package implementing interactive graphics for exploratory spatial data analysis. We use data bases coming from the spdep package to illustrate the use of these exploratory techniques based on the coupling between a statistical graph and a map. Besides elementary plots like boxplots, histograms or simple scatterplots, GeoXp also(More)
We consider a nonparametric random design regression model in which the response variable is possibly right censored. The aim of this paper is to estimate the conditional distribution function and the conditional alpha-quantile of the response variable. We restrict attention to the case where the response variable as well as the explanatory variable are(More)
The solution of differential equations lies at the heart of many problems in structural economics. In econometrics the general nonparametric analysis of consumer welfare is historically the most obvious application, but there are also many in finance and other fields. This work considers the general nonparametric form for these problems and identification(More)
We address the problem of prediction in the classical spatial autoregressive LAG model for areal data. In contrast with the spatial econometrics literature, the geostatistical literature has devoted much attention to prediction using the Best Linear Unbiased Prediction approach. From the methodological point of view, we explore the limits of the extension(More)
Abstract The Mahalanobis distance between pairs of multivariate observations is used as a measure of similarity between the observations. The theoretical distribution is derived, and the result is used for judging on the degree of isolation of an observation. In case of spatially dependent data where spatial coordinates are available, different exploratory(More)
  • 1