On binary and categorical time series models with feedback
On binary and categorical time series models with feedback
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DOI：
10.1016/j.jmva.2014.07.004
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发表时间：
2014-10-01
影响因子：
1.6
通讯作者：
Fokianos, Konstantinos
中科院分区：
文献类型：
--
作者：
Moysiadis, Theodoros;Fokianos, Konstantinos
研究了包含潜在过程的多项逻辑模型的遍历性、平稳性和极大似然估计问题。我们的工作包括已提出的各种模型，用于分析二进制和更一般的分类时间序列。我们给出了这类时间序列数据分析的可验证的遍历性和平稳性条件。此外，我们还研究了极大似然估计，并证明了在温和条件下，估计量是渐近正态分布的。这些结果应用于实际数据和模拟数据。(C) 2014爱思唯尔公司版权所有。
We study the problem of ergodicity, stationarity and maximum likelihood estimation for multinomial logistic models that include a latent process. Our work includes various models that have been proposed for the analysis of binary and, more general, categorical time series. We give verifiable ergodicity and stationarity conditions for the analysis of such time series data. In addition, we study maximum likelihood estimation and prove that, under mild conditions, the estimator is asymptotically normally distributed. These results are applied to real and simulated data. (C) 2014 Elsevier Inc. All rights reserved.