Empirical likelihood for linear models under m-dependent errors
Tóm tắt
In this paper, the empirical likelihood confidence regions for the regression coefficient in a linear model are constructed under m-dependent errors. It is shown that the blockwise empirical likelihood is a good way to deal with dependent samples.
Tài liệu tham khảo
Yu Zhaoping, Tu Dongsheng. Convergence rates of Bootstrap and random weighted approximation for the mean of a m-dependent sample, Appl Math J Chinese Univ, 1993, 8:396–402.
Owen A B. Empirical likelihood ratio confidence intervals for a single functional, Biometrika, 1988, 75:237–249.
Owen A B. Empirical likelihood confidence regions, Ann Statist, 1990, 18:90–120.
Owen A B. Empirical likelihood for linear models, Ann Statist, 1991, 19:1725–1747.
Chen S X. On the accuracy of empirical likelihood confidence regions for linear regression models, Ann Inst Statist Math, 1993, 45:621–637.
Chen S X. Comparing empirical likelihood and bootstrap hypothesis tests, J Multivariate Anal, 1994, 51:277–293.
Chen S X. Empirical likelihood confidence intervals for linear regression coefficients, J Multivariate Anal, 1994, 49:24–40.
Qin J, Lawless J. Empirical likelihhod and general estimating equations, Ann Statist, 1994, 23:300–325.
Kitamura Y. Empirical likelihood methods with weakly dependent processes, Ann Statist, 1997, 25: 2084–2102.
Zhang Junjian, Wang Chengming, Wang Weixin. Empirical likelihood ratio confidence regions for dependent samples, Appl Math J Chinese Univ Ser A, 1999, 14:63–72.
Shi X Q. Bootstrap estimation for the mean of a m-dependent sample, Chinese Science Bulletin, 1986, 6:404–407.