主  題：Functional linear models with fixed effects

內容簡介：In this paper, we introduce a functional linear model with fixed effects for functional data where the predictor and response are random processes. The proposed model can be viewed as a generalization of the classical functional linear model, and characterizes individual specific source of variability. We implement the regularity procedure through a projection on the eigenfunction basis of the response process, leading to a special version of linear mixed effects model for panel data. In order to deal with the difficulty caused by a large number of individual effects, we use the penalty method to shrink individual effects, and propose a class of penalized least squares estimators. In a theoretical investigation, we establish asymptotic normality for the deviation between estimated and true regression function coefficients, and derive some asymptotic consistent properties for the predictions obtained from the fitted functional linear models with fixed effects.  Some simulation studies and an application of intra-day volatility patterns of the $S/&P$ 500 index are conducted to illustrate the finite sample performance of the proposed modeling framework and estimation methods.

報告人：朱仲義    教授    博導

                    “應用概率統計”,”數理統計與管理”雜志編委

                     中國現場統計研究會常務理事

                     中國統計教材編審委員會委員

時  間：    2016-06-03    13:30

地  點：競慧東樓302

舉辦單位：理學院  科研部