R routines for performing estimation and statistical process control under copula-based time series models

DOI10.1080/03610918.2015.1073303zbMath1373.62583OpenAlexW2195125035MaRDI QIDQ5358361

Li-Hsien Sun, Takeshi Emura, Ting-Hsuan Long

Publication date: 20 September 2017

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2015.1073303

zbMATH Keywords

Newton-Raphson algorithmClayton copulaShewhart control chartJoe copula

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Software, source code, etc. for problems pertaining to statistics (62-04) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Measures of association (correlation, canonical correlation, etc.) (62H20) Applications of statistics in engineering and industry; control charts (62P30)

Related Items

Bivariate copula-based CUSUM charts for monitoring conditional nonlinear processes with first-order autocorrelation, A Bayesian inference for time series via copula-based Markov chain models, Control charts of mean and variance using copula Markov SPC and conditional distribution by copula, Nonlinear independent component analysis for discrete-time and continuous-time signals, Unnamed Item, Model diagnostic procedures for copula-based Markov chain models for statistical process control, Estimation under copula-based Markov normal mixture models for serially correlated data, Copula.Markov, Goodness-of-fit test of copula functions for semi-parametric univariate time series models, A copula-based Markov chain model for serially dependent event times with a dependent terminal event

Uses Software

• R