题目：Least Squares Estimation for Nonlinear Regression Models with Heteroscedasticity
报告人：Prof. Wang Qiying（悉尼大学数学与统计学院）
摘要：This paper develops an asymptotic theory for general nonlinear regression models, establishing a new framework on least squares estimation that is easy to apply for various nonlinear regression models with heteroscedasticity. This paper explores an application of the framework to nonlinear regression models with nonstationarity and heteroscedasticity. Accompanying with these main results, this paper provides a maximum inequality for a class of martingales and establishes some new results on convergence to a local time and convergence to a mixture of normal distributions, which are interested in their own rights.
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