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主讲人 |
Ying Chen |
简介 |
<p>We propose an Adaptive Functional Autoregressive (AFAR) forecast model to predict electricity price curves. With time-varying operators, the AFAR model can be safely used in both stationary and non-stationary situations. A closed-form maximum likelihood (ML) estimator is derived under stationarity. The result is further extended for non-stationarity, where the time-dependent operators are adaptively estimated under local homogeneity. We provide the theoretical results of the ML estimator and the adaptive estimator. Simulation study illustrates nice finite sample performance of the AFAR modeling. The AFAR model also exhibits a superior accuracy in the forecast exercise of the California electricity daily price curves compared to several alternatives.</p> |
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主讲人简介 |
<p>Associate professor in Department of Statistics and Applied Probability, National University of Singapore</p>
<p><a href="/EventsMgr/Upload/File/2015/9/20150918070807653.pdf"><u>CV</u></a></p> |
期数 |
厦门大学高级计量经济学与统计学系列讲座2015秋季学期第一讲（总第64讲） |
