标题： 函数空间中的动态多重回归，基于核回归器，具有ARH(1)误差 显示英文标题

标题： Dynamical multiple regression in function spaces, under kernel regressors, with ARH(1) errors

摘要： 一个在函数空间中的线性多重回归模型被提出，该模型在时间相关的误差下进行。 这种表述涉及核回归器。 推导出广义的最小二乘回归参数估计器。 在适当的条件下，得到了它的渐近正态性和强一致性。 相关性分析基于残差自相关算子的分量估计器。 当函数误差项的依赖结构未知时，提出了一个嵌入式的广义最小二乘回归参数估计器。 也证明了它的强一致性。 进行了模拟研究以说明在不同正则条件下的表现。 还考虑了对金融面板数据的应用。 显示英文摘要

摘要： A linear multiple regression model in function spaces is formulated, under temporal correlated errors. This formulation involves kernel regressors. A generalized least-squared regression parameter estimator is derived. Its asymptotic normality and strong consistency is obtained, under suitable conditions. The correlation analysis is based on a componentwise estimator of the residual autocorrelation operator. When the dependence structure of the functional error term is unknown, a plug-in generalized least-squared regression parameter estimator is formulated. Its strong-consistency is proved as well. A simulation study is undertaken to illustrate the performance of the presented approach, under different regularity conditions. An application to financial panel data is also considered.