报告主题：Gegenbauer processes and energy informatics
报告人：YangQuan Chen 教授 （University of California, Merced）
报告时间：2019年7月29日（周一）9:00
报告地点：校本部G508
邀请人：李常品
报告摘要： Gegenbauer polynomial has a generating function of a real power of a quadratic polynomial. When this quadratic polynomial is the z-transfer function of a second order IIR or FIR, raising this whole z-transfer function to the power of a real number, we will get an irrational z-transfer function whose output is called the Gegenbauer process driven by white noise. It turns out that, Gegenbauer process can exhibit both long range dependence (or long memory) and seasonality. This is particularly attractive in modeling time series in energy informatics such as wind speed, power consumption, energy price etc. where long memory and seasonality both dominate. In this seminar, we will introduce this important yet relatively new class of models known as k-factor Gegenbauer ARMA and its applications in time series modeling and prediction in energy informatics.
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