NCSU, Princeton University, and UC-Davis Abstract: Functional linear regression analysis aims to model regression relations which include a functional predictor. The analogue to the regression parameter vector or matrix in conventional multivariate or multiple-response linear regression models is a regression parameter function in one or two arguments. If in addition one has scalar predictors, ...

We propose in this work a generalization of the functional linear model in which an additional real variable influences smoothly the functional coefficient. This leads us to build a varying-coefficient regressionmodel for functional data. We propose two estimators based respectively on conditional functional principal regression and on local penalized regression splines and prove their pointwis...

This article considers the quantile regression approach for partially linear spatial autoregressive models with possibly varying coefficients. B-spline is employed approximation of The instrumental variable parameter estimation. rank score tests are developed hypotheses on coefficients, including non-varying coefficients and constancy asymptotic properties proposed estimators test statistics bo...