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The first-order random coefficient integer valued autoregressive process with the occasional level shift random noise based on dual empirical likelihood

机译:一阶随机系数整数重度自回归过程,偶尔的水平换档随机噪声基于双重经验似然性

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摘要

This paper investigates the first-order random coefficient integer valued autoregressive process with the occasional level shift random noise based on dual empirical likelihood. The limiting distribution of log empirical likelihood ratio statistic is constructed. Asymptotic convergence and confidence region results of empirical likelihood ratio are given. Hypothesis testing is considering, and maximum empirical likelihood estimation for parameter is acquired. Simulations are given to show that the maximum empirical likelihood estimation is more efficient than the conditional least squares estimation.
机译:本文研究了一阶随机系数整数重度自回归过程,基于双重经验似然,偶尔的水平换档随机噪声。构建了日志经验似然比统计的限制分布。给出了渐近收敛和置信区的经验似然比。假设测试正在考虑,获取参数的最大经验似然估计。给出了模拟,表明最大的经验似然估计比条件最小二乘估计更有效。

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