Weighted least absolute deviations estimation for ARFIMA time series with finite or infinite variance

被引：0

作者：

Baoguo Pan

Min Chen

Yan Wang

Wei Xia

机构：

[1] Hubei engineering University,Academy of Mathematics and Statistics

[2] University of Chinese Academy of Sciences,Academy of Mathematics and Systems Science

[3] Capital University of Economics and Finance,School of Statistics

[4] University of Science and Technology of China,School of Mathematics and Statistics

来源：

Journal of the Korean Statistical Society | 2015年 / 44卷

关键词：

primary 62M10; 62F12; secondary 62F05; ARFIMA; WLAD; Asymptotic normality; Stationarity; Testing;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In this paper a weighted least absolute deviations (WLAD) estimator for fractionally autoregressive integrated moving average (ARFIMA) models is proposed, in which stationary and non-stationary cases are discussed. The asymptotic normality of their local estimators is derived under a fractional moment condition. A Wald test for a linear hypothesis has been constructed, its limiting distribution is presented, and a simulation study is given to evaluate the performance of the proposed WLAD estimator under the stationary case.

引用

页码：1 / 11

页数：10

共 30 条

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