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A New Bivariate Binomial Time Series Model

机译:新的二元二项式时间序列模型

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In this manuscript we introduce a new bivariate time series model whose both components have identical binomial distributions. We study some properties of the model and prove that the model is strictly stationary and ergodic. The correlation structure of the model is presented and thereafter we study different estimation procedures such as Yule -Walker, conditional least squares and conditional maximum likelihood. Simulation studies show that the best estimates in the sense of lower standard deviations are obtained by the maximum likelihood estimation method. We show that the model can be used as a good choice for modelling the number of rainfall days per week. The paper ends with a discussion of a possible extension of the introduced model.
机译:在本手稿中,我们介绍了一个新的双变量时间序列模型,该模型的两个分量都具有相同的二项式分布。我们研究了该模型的一些特性,并证明该模型严格是平稳的和遍历的。提出了模型的相关结构,然后我们研究了不同的估计程序,例如Yule -Walker,条件最小二乘和条件最大似然。仿真研究表明,通过最大似然估计方法可以获得较低标准偏差的最佳估计。我们表明,该模型可以用作建模每周降雨天数的理想选择。本文最后讨论了引入模型的可能扩展。

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