R routines for performing estimation and statistical process control under copula-based time series models |
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Authors: | Takeshi Emura Ting-Hsuan Long Li-Hsien Sun |
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Affiliation: | Graduate Institute of Statistics, National Central University, Zhongli, Taoyuan, Taiwan |
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Abstract: | Modeling serial dependence in time series is an important step in statistical process control. We provide a set of automatic routines useful for simulating and analyzing time series under a copula-based serial dependence. First, we introduce routines that generate time series data under a given copula. Second, we provide fully automated routines for obtaining maximum likelihood estimates for given time series data and then drawing a Shewhart-type control chart. Finally, real data are analyzed for illustration. We make the routines available as “Copula.Markov” package in R. |
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Keywords: | Clayton copula Joe copula Newton–Raphson algorithm Shewhart control chart |
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