tscount: An R Package for Analysis of Count Time Series Following Generalized Linear Models
tscount: An R Package for Analysis of Count Time Series Following Generalized Linear Models
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DOI：
10.18637/jss.v082.i05
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发表时间：
2017-11-01
影响因子：
5.8
通讯作者：
Fried, Roland
中科院分区：
文献类型：
--
作者：
Liboschik, Tobias;Fokianos, Konstantinos;Fried, Roland
R软件包tscount提供了基于似然的估计方法，用于分析和建模广义线性模型下的计数时间序列。这是一类灵活的模型，可以以简约的方式描述序列相关性。过程的条件均值与其过去值、过去观测值和潜在协变量效应相关。该软件包允许模型的身份和对数链接功能。条件分布可以是泊松分布或负二项分布。这类的一个重要特例是所谓的INGARY模型及其对数线性扩展。该软件包包括模型拟合和评估、预测和干预分析的方法。本文综述了这些方法的理论背景。它给出了详细的实施方案，并提供了模型的仿真结果，没有被理论研究之前。通过两个数据实例说明了该软件包的使用方法。此外，我们还提供了一个可用于计数时间序列分析的R包的回顾。这包括tscount与这些包的详细比较。
The R package tscount provides likelihood-based estimation methods for analysis and modeling of count time series following generalized linear models. This is a flexible class of models which can describe serial correlation in a parsimonious way. The conditional mean of the process is linked to its past values, to past observations and to potential covariate effects. The package allows for models with the identity and with the logarithmic link function. The conditional distribution can be Poisson or negative binomial. An important special case of this class is the so-called INGARCH model and its log-linear extension. The package includes methods for model fitting and assessment, prediction and intervention analysis. This paper summarizes the theoretical background of these methods. It gives details on the implementation of the package and provides simulation results for models which have not been studied theoretically before. The usage of the package is illustrated by two data examples. Additionally, we provide a review of R packages which can be used for count time series analysis. This includes a detailed comparison of tscount to those packages.