A new skew integer valued time series process

Q Mathematics

Statistical Methodology Pub Date : 2016-07-01 DOI:10.1016/j.stamet.2016.01.002

Marcelo Bourguignon , Klaus L.P. Vasconcellos

引用次数: 10

Abstract

In this paper, we introduce a stationary first-order integer-valued autoregressive process with geometric–Poisson marginals. The new process allows negative values for the series. Several properties of the process are established. The unknown parameters of the model are estimated using the Yule–Walker method and the asymptotic properties of the estimator are considered. Some numerical results of the estimators are presented with a brief discussion. Possible application of the process is discussed through a real data example.

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一种新的斜整数值时间序列过程

本文引入了一类具有几何泊松边缘的一阶平稳整值自回归过程。新的处理方法允许该级数为负值。确定了该工艺的几个特性。利用Yule-Walker方法对模型的未知参数进行了估计，并考虑了估计量的渐近性质。给出了一些估计量的数值结果，并进行了简要讨论。通过一个实际的数据实例，讨论了该方法的可能应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Statistical Methodology STATISTICS & PROBABILITY-

CiteScore

0.59

自引率

0.00%

发文量

期刊介绍： Statistical Methodology aims to publish articles of high quality reflecting the varied facets of contemporary statistical theory as well as of significant applications. In addition to helping to stimulate research, the journal intends to bring about interactions among statisticians and scientists in other disciplines broadly interested in statistical methodology. The journal focuses on traditional areas such as statistical inference, multivariate analysis, design of experiments, sampling theory, regression analysis, re-sampling methods, time series, nonparametric statistics, etc., and also gives special emphasis to established as well as emerging applied areas.