报告题目：在连续时间分析中使用函数数据分析方法的拟合和预测

报告人：田人方（西安大略大学国王大学公司）

报告时间：2023年7月3日（星期一）上午10：30—11：30

报告地点：威斯尼斯人老品牌官网大楼318会议室

邀请部门：经济学系

报告人简介：

田人方，加拿大滑铁卢大学经济学博士，现任西安大略大学国王大学公司MEM经济学助理教授，研究方向为计量经济学和函数数据分析（functional data analysis）。近期开始研究计量经济学和统计学方法在健康学习中的推广和应用。

报告摘要：

Parametric continuous-time analysis for stochastic processes often entails the generalization of a predefined discrete formulation to a continuous-time limit. However, unknown convergence rates of the frequency-dependent parameters can destabilize the continuous-time generalization and cause modeling discrepancy, which in turn leads to unreliable estimation and forecast. To circumvent this discrepancy, we propose a simple solution for fitting and forecasting in continuous-time analysis based on functional data analysis and truncated Taylor series expansions. It is demonstrated through a simulation that our proposed method is superior in both fitting and forecasting continuous-time stochastic processes compared with traditional parametric methods that encounter troubles uncovering the true underlying processes.