时间：2016年6月2日（周四）15：30- 17：00
地点：旗山校区理工北楼601报告厅
主办：数学与计算机科学学院、福建省分析数学及应用重点实验室、数学研究中心
主讲：南开大学 程婷婷博士
专家简介：程婷婷，2015年毕业于澳大利亚莫纳什大学计量与商务统计系获得博士学位，南开大学金融学院助理教授。
报告摘要：This paper studies a functional coefficient time series model with trending regressors, where the coefficients are unknown functions of time and random variables. We propose a local linear estimation method to estimate the unknown coefficient functions. An asymptotic distribution of the proposed local linear estimator is established under mild conditions. For practical use, we further propose a Bayesian approach to select bandwidths involved in this local linear estimator. Several numerical examples are provided to examine the finite sample performance of the proposed local linear estimator. The results show that the local linear estimator works well and the Bayesian bandwidth selection method is better than cross–validation method. Furthermore, we employ the functional coefficient model to study the relationship between consumption per capita and income per capita in U.S. and the results show that functional coefficient model with our proposed local linear estimator and Bayesian bandwidth selection method performs best in both in–sample fitting and out–of–sample forecasting.