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arXiv 2207.07069math.PR
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非负性假设下随机系数AR($\infty$)的矩条件

Moment conditions for random coefficient AR($\infty$) under non-negativity assumptions

Pascal Maillard, Olivier Wintenberger

AI总结:

该研究针对非负系数的无限阶随机系数自回归模型AR($\infty$),基于一二阶矩的组合表达式提出推导矩有限性充要/充分条件的新方法,复现了已有结果并验证了有限阶下与经典准则的等价性,辅以示例说明。

摘要:

我们研究系数非负假设下的无限阶随机系数自回归模型(AR($\infty$))。基于一阶矩和二阶矩的组合表达式,我们提出了推导矩有限性的充分或必要条件的新方法。基于一阶矩的方法在我们的设定下复现了Doukhan和Wintenberger先前提出的充分条件。二阶矩方法尤其给出了二阶矩有限性的充要条件,该条件虽有不同,但在有限阶情形下等价于Nicholls和Quinn的经典准则。我们还通过两个示例进一步说明了所得结果。

英文摘要:

We consider random coefficient autoregressive models of infinite order (AR($\infty$)) under the assumption of non-negativity of the coefficients. We develop novel methods yielding sufficient or necessary conditions for finiteness of moments, based on combinatorial expressions of first and second moments. The methods based on first moments recover previous sufficient conditions by Doukhan and Wintenberger in our setting. The second moment method provides in particular a necessary and sufficient condition for finiteness of second moments which is different, but shown to be equivalent to the classical criterion of Nicholls and Quinn in the case of finite order. We further illustrate our results through two examples.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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