TIME SERIES ANALYSIS IN PERSPECTIVE
TIME SERIES ANALYSIS IN PERSPECTIVE
复制标题
透视时间序列分析
DOI：
10.1111/j.1752-1688.1985.tb05376.x
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发表时间：
1985
期刊：
影响因子：
--
通讯作者：
K. Hipel
中科院分区：
文献类型：
--
作者：
K. Hipel
摘要：通过采用一组标准对时间序列模型的功能进行分类，对时间序列分析的最新发展进行了评估并进行了正确的审视。特别是，本书中 18 篇论文的作者提出的各种时间序列模型和建模程序的固有属性都得到了明确的指出。此外，还解释了这些模型如何解决在对水文、水质和其他类型的时间序列进行建模时遇到的许多时间序列问题。例如，时间序列模型系列现在可用于对可能包含非线性或可能遵循非高斯分布的序列进行建模。基于对问题的良好物理理解和探索性数据分析的结果，可以通过遵循模型构建的识别、估计和诊断检查阶段，在验证性数据分析期间找到适合数据集的最合适的模型。建议未来有前途的研究项目开发用于水资源应用的灵活类别的时间序列模型。
ABSTRACT: By employing a set of criteria for classifying the capabilities of time series models, recent developments in time series analysis are assessed and put into proper perspective. In particular, the inherent attributes of a wide variety of time series models and modeling procedures presented by the authors of the 18 papers contained in this volume are clearly pointed out. Additionally, it is explained how these models can address many of the time series problems encountered when modeling hydrologic, water quality and other kinds of time series. For instance, families of time series models are now available for modeling series which may contain nonlinearities or may follow nonGaussian distributions. Based upon a sound physical understanding of a problem and results from exploratory data analyses, the most appropriate model to fit to a data set can be found during confirmatory data analyses by following the identification, estimation and diagnostic check stages of model construction. Promising future research projects for developing flexible classes of time series models for use in water resources applications are suggested.