方差可能无穷的“中度偏离”单位根过程的复合分位数估计

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英文篇名：Composite quantile estimation for moderate deviations from a unit root model with possibly infinite variance errors 作者：倪佳林 ; 傅可昂 英文作者：NI Jia-lin;FU Ke-ang;School of Stat.and Math.,Zhejiang Gongshang Univ.; 关键词：自回归 ; 单位根 ; 正态吸引场 ; 重尾 ; 复合分位数 英文关键词：autoregression;;unit root;;domain of attraction of the normal law;;heavy tail;;composite quantile estimation 中文刊名：GXYZ 英文刊名：Applied Mathematics A Journal of Chinese Universities(Ser.A) 机构：浙江工商大学统计与数学学院; 出版日期：2017-03-15 出版单位：高校应用数学学报A辑 年：2017 期：v.32 基金：浙江省自然科学基金(LY17A010004);; 浙江省统计局2016年度统计研究课题;; 浙江工商大学研究生科研创新基金项目;; 浙江省一流学科A类(浙江工商大学统计学);; 浙江省高校人文社科重点研究基地(统计学) 语种：中文; 页：GXYZ201701005 页数：8 CN：01 ISSN：33-1110/O 分类号：45-52

摘要

考虑一类"中度偏离"单位根过程,y_t=q_ny_t-1+u_t,其中qn=1+c/(k_n),k_n=o(n),c为一非零常数,{u_t}为随机扰动项序列.在允许扰动项方差无穷的条件下,构造q_n的复合分位数估计,并得到了该估计的渐近分布.最后通过数值模拟,在扰动项服从t(2)分布下,说明了该估计的稳健和有效性.
        Under the mildly integrated and the mildly explosive cases, the asymptotic distributions of composite quantile estimation for moderate deviations from a unit root model with possibly infinite variance errors are obtained, respectively. Some simulation studies are also given to show that the composite quantile estimation has a good performance.

引文

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