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扩散模型复合分位回归估计的渐近正态性 被引量：2

Asymptotic Normality of Composite Quantile Regression Estimation for Diffusion Model
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摘要 主要研究扩散模型中漂移函数的复合分位回归估计的渐近正态性.基于离散观测样本,利用复合分位回归的方法得到了漂移参数函数的局部估计量,并证明了估计量的渐近正态性. This paper studies asymptotic normality of the composite quantile regression estimation of the drift function for diffusion model. Based on discretely ohserved sample of the diffusion models, the local estimation of the drift parametric functions are gained by using composite quantile regression method, and the asymptotic normality of the estimation that we pro- posed is verified.
作者 王继霞 肖庆宪
机构地区 上海理工大学管理学院 河南师范大学数学与信息科学学院
出处 《河南师范大学学报（自然科学版）》 CAS 北大核心 2014年第2期25-28,共4页 Journal of Henan Normal University(Natural Science Edition)
基金 国家自然科学基金(11171221) 上海市一流学科(系统科学)项目资助(XTKX2012)
关键词 扩散模型 漂移函数 复合分位回归估计 渐近正态性 diffusion model drift function composite quantile regression estimation asymptotic normality
分类号 O212.1 [理学—概率论与数理统计]
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参考文献8

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共引文献5

同被引文献15

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引证文献2

二级引证文献2

河南师范大学学报（自然科学版）
2014年 第2期

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