Local polynomial estimations of time-varying coefficients for local stationary diffusion models

被引：0
|
作者：
Wang, Jixia [1 ,2 ]
Xiao, Qingxian [1 ]
机构：
[1] Shanghai Univ Sci & Technol, Business Sch, Shanghai 200093, Peoples R China
[2] Henan Normal Univ, Coll Math & Informat Sci, Xinxiang 453007, Henan, Peoples R China
来源：
JOURNAL OF INEQUALITIES AND APPLICATIONS | 2014年
基金：
中国国家自然科学基金;
关键词：
local stationary model; local polynomial fitting; consistency; asymptotic normality; convergence rate; UNIFORM-CONVERGENCE RATES; DEPENDENT DATA; SERIES;
D O I：
10.1186/1029-242X-2014-17
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper is dedicated to the study of local polynomial estimations of time-varying coefficients for a local stationary diffusion model. Based on local polynomial fitting, the estimations of drift parametric functions are obtained by using local weighted least squares method. By applying the forward Kolmogorov equation, the estimation of the diffusion coefficient is proposed. The consistency, asymptotic normality and uniform convergence of the estimations that we proposed are established.
引用
收藏
页数：11
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