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.
Original language | English |
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Pages (from-to) | 3067-3087 |
Number of pages | 21 |
Journal | Communications in Statistics - Simulation and Computation |
Volume | 46 |
Issue number | 4 |
DOIs | |
State | Published - 21 Apr 2017 |
Keywords
- Clayton copula
- Joe copula
- Newton–Raphson algorithm
- Shewhart control chart