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Estimation on semivarying coefficient models with different degrees of smoothness
Authors:Riquan Zhang  Jingyan Feng  Kaichun Wen  Jianhua Ding
Institution:(1) Department of Statistics, East China Normal University, Shanghai, 200241, China;(2) Department of Mathematics, Shanxi Datong University, Datong, 037009, China;(3) Dagang No. 1 Middle School of Tianjin, Tianjin, 300270, China
Abstract:Semivarying coefficient models are frequently used in statistical models. In this paper, under the condition that the coefficient functions possess different degrees of smoothness, a two-step method is proposed. In the case, one-step method for the smoother coefficient functions cannot be optimal. This drawback can be repaired by using the two-step estimation procedure. The asymptotic mean-squared error for the two-step procedure is obtained and is shown to achieve the optimal rate of convergence. A few simulation studies are conducted to evaluate the proposed estimation methods. This research is supported in part by the National Natural Science Foundation of China under Grant No. 10871072 and Shanxi's Natural Science Foundation of China under Grant No. 2007011014.
Keywords:Local polynomial regression  one-step estimation  optimal rate of convergence  semi-varying coefficient model  two-step estimation
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