Learn More
▶ Definitive text for graduate or advanced undergraduate students seeking a self-contained introduction to the subject ▶ Advanced researchers will benefit from novel asymptotic arguments ▶ All procedures described algorithmically, illustrated on simulated and real data sets, and supported by a complete asymptotic theory This book presents recently developed(More)
We study the almost sure convergence of the Bartlett estimator for the asymp-totic variance of the sample mean of a stationary weekly dependent process. We also study the a. s. behavior of this estimator in the case of long-range dependent observations. In the weakly dependent case, we establish conditions under which the estimator is strongly consistent.(More)
The paper develops a comprehensive asymptotic theory for the estimation of a change– point in the mean function of functional observations. We consider both the case of a constant change size, and the case of a change whose size approaches zero, as the sample size tends to infinity. We show how the limit distribution of a suitably defined change– point(More)
AMS subject classifiactions: 62H15 62H25 Keywords: Functional data Change in mean Increasing dimension Normal approximation Principal components a b s t r a c t Functional principal components (FPC's) provide the most important and most extensively used tool for dimension reduction and inference for functional data. The selection of the number, d, of the(More)