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Estimation and Influence Diagnostics for INGARCH models

来源:上海立信会计金融学院   点击率:
 

时间:20181217日(周一)10:20-11:00

地点:浦东校区第一教学大楼204会议室

讲座题目:Estimation and Influence Diagnostics for INGARCH models

内容摘要:

In statistical diagnostics and sensitivity analysis, the local influence method plays an important role and has certain advantages over other methods in several situations. In this talk, we use this method to study time series of count data when employing integer-valued generalized autoregressive conditional heteroscedasticity (GARCH) models. We consider case-weights, scale, data, and additive perturbation schemes to obtain their corresponding vectors and matrices of derivatives for the measures of slope and normal curvatures. Based on the curvature diagnostics, we take a stepwise local influence approach to deal with data with possible masking effects. Finally, our established results are illustrated to be effective by analyzing a stock transactions data set.

报告人简介:

刘双喆教授为澳大利亚堪培拉大学工程,数学与统计学院教授。毕业于阿姆斯特丹大学丁伯根学院获计量经济博士学位,从事矩阵微分,计量经济,数理统计,统计诊断,时序分析,数据科学的教学和科研工作多年,并在矩阵微分,统计诊断和时序分析等领域具有出色贡献和国际影响。目前担任国际期刊Journal of Applied Statistics, Journal of Statistical Computation and Simulation, Statistical Papers, Chilean Journal of Statistics的副主编。在BiometrikaJournal of Econometrics等国际期刊发表论文100余篇。出版英文专著6部,Book Chapter 15项。曾获上海市海外名师项目(上海对外经贸大学:2014-20152016-2017)。

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