半参数平滑转换回归模型及其级数估计

Abstract

Abstract:

An unknown smooth function is substituted into the traditional smooth transition regression model and a semiparametric smooth transition regression model has been proposed in this paper. Based on the i.i.d. data assumption, we estimate the unknown smooth transition function by series estimator, the consistency and asymptotic normality properties of parameters are proved applying Nonlinear Least Square regression theory. The bootstrapping consistent confidence interval and hypothesis testing problem are also discussed briefly. The simulation results shows that, compared to traditional STR type model, our new model and estimating method are more flexible and have comprehensive applicability.

Key words: Smooth Transition Regression Model, Series Estimator, Consistency, Asymptotic Normality, Simulation

CLC Number:

62G08

WANG Cheng-Yong. A Semiparametric Smooth Transition Regression Model and Its Series Estimator[J].Acta mathematica scientia,Series A, 2012, 32(4): 797-807.

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A Semiparametric Smooth Transition Regression Model and Its Series Estimator

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