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首页> 外文期刊>Journal of applied statistics >Bootstrap unit root test based on least absolute deviation estimation under dependence assumptions
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Bootstrap unit root test based on least absolute deviation estimation under dependence assumptions

机译:在依赖假设下基于最小绝对偏差估计的自举单元根测试

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摘要

In this paper, a bootstrap test based on the least absolute deviation (LAD) estimation for the unit root test in first-order autoregressive models with dependent residuals is considered. The convergence in probability of the bootstrap distribution function is established. Under the frame of dependence assumptions, the asymptotic behavior of the bootstrap LAD estimator is independent of the covariance matrix of the residuals, which automatically approximates the target distribution.
机译:在本文中,考虑了基于最小绝对偏差(LAD)估计的自举测试,用于一阶自回归模型中具有相关残差的单位根检验。自举分布函数的概率收敛。在依赖假设的框架下,自举LAD估计器的渐近行为与残差的协方差矩阵无关,后者自动近似目标分布。

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