| ARCH(0,1)系数中位无偏估计分布的渐近展开 |
| |
| 引用本文： | 王德辉.ARCH(0,1)系数中位无偏估计分布的渐近展开[J].东北数学,2007,23(2):176-188. |
| |
| 作者姓名： | 王德辉 |
| |
| 作者单位： | [1]School of Mathematics, Jilin University, Changchun, 130012 [2]Department of Mathematics, Shimane University, Matsue, Japan, 690-8504 |
| |
| 摘 要： | This paper is concerned with the distributional properties of a median unbiased estimator of ARCH（0,1） coefficient. The exact distribution of the estimator can be easily derived, however its practical calculations are too heavy to implement, even though the middle range of sample sizes. Since the estimator is shown to have asymptotic normality, asymptotic expansions for the distribution and the percentiles of the estimator are derived as the refinements. Accuracies of expansion formulas are evaluated numerically, and the results of which show that we can effectively use the expansion as a fine approximation of the distribution with rapid calculations. Derived expansion are applied to testing hypothesis of stationarity, and an implementation for a real data set is illustrated.
|
| 关 键 词： | 渐进线扩展 渐进线分布 Edgeworth扩展 Cornish-Fisher扩展 |
| 文章编号： | 1000-1778（2007）02-0176-13 |
| 收稿时间： | 2006-10-20 |
| 修稿时间： | 2006-10-20 |
Asymptotic Expansion for the Distribution of a Median Unbiased Estimator of ARCH(0,1) Coefficient |
| |
| Kanta Naito,WANG De-hui,Kanta Naito.Asymptotic Expansion for the Distribution of a Median Unbiased Estimator of ARCH(0,1) Coefficient[J].Northeastern Mathematical Journal,2007,23(2):176-188. |
| |
| Authors: | Kanta Naito WANG De-hui Kanta Naito |
| |
| Institution: | 1.School of Mathematics, Jilin University, Changchun, 130012;2.Department of Mathematics, Shimane University, Matsue, Japan, 690-8504 |
| |
| Abstract: | This paper is concerned with the distributional properties of a median unbiased estimator of ARCH(0,1) coefficient. The exact distribution of the estimator can be easily derived, however its practical calculations are too heavy to implement,even though the middle range of sample sizes. Since the estimator is shown to have asymptotic normality, asymptotic expansions for the distribution and the percentiles of the estimator are derived as the refinements. Accuracies of expansion formulas are evaluated numerically, and the results of which show that we can effectively use the expansion as a fine approximatioh of the distribution with rapid calculations. Derived expansion are applied to testing hypothesis of stationarity, and an implementation for a real data set is illustrated. |
| |
| Keywords: | ARCH(0 1) process asymptotic distribution Cornish-Fisher expansion Edgeworth expansion median unbiased |
| 本文献已被 维普 万方数据 等数据库收录！ |
|
