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Monitoring multistage processes with autocorrelated observations
International Journal of Production Research, 2016 In multistage manufacturing processes, autocorrelations within stages over time are prevalent and the classical control charts are often ineffective in monitoring such processes. In this paper, we derive a linear state space model of an autocorrelated multistage process as a vector autoregressive process, and construct novel multivariate control charts,
Kim, Jinho +2 more
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Monitoring the Zero-Inflated Time Series Model of Counts with Random Coefficient
Entropy, 2021 In this research, we consider monitoring mean and correlation changes from zero-inflated autocorrelated count data based on the integer-valued time series model with random survival rate.
Cong Li, Shuai Cui, Dehui Wang
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Subsampling Inference for the Autocorrelations of GARCH Processes*
Journal of Financial Econometrics, 2017 AbstractWe provide self-normalization for the sample autocorrelations of power GARCH(p, q) processes whose higher moments might be infinite. To validate the studentization, whose goal is to match the growth rate dependent on the index of regular variation of the process, we substantially extend existing weak-convergence results.
McElroy, Tucker, Jach, Agnieszka
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International Journal of Mathematics and Mathematical Sciences, 2022 Fitting a time series model to the process data before applying a control chart to the residuals is essential to fulfill the basic assumptions of statistical process control (SPC).
Siaw Li Lee +3 more
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Abstract and Applied Analysis, 2014 Because of the excellent performance on monitoring and controlling an autocorrelated process, the integration of statistical process control (SPC) and engineering process control (EPC) has drawn considerable attention in recent years.
Yuehjen E. Shao
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The GLRT for statistical process control of autocorrelated processes [PDF]
IIE Transactions, 1999 This paper presents an on-line Statistical Process Control (SPC) technique, based on a Generalized Likelihood Ratio Test (GLRT), for detecting and estimating mean shifts in autocorrelated processes that follow a normally distributed Autoregressive Integrated Moving Average (ARIMA) model.
Apley, Daniel W., Shi, Jianjun
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Autocorrelation of the susceptible-infected-susceptible process on networks [PDF]
Physical Review E, 2018 In this paper, we focus on the autocorrelation of the susceptible-infected-susceptible (SIS) process on networks. The N-intertwined mean-field approximation (NIMFA) is applied to calculate the autocorrelation properties of the exact SIS process. We derive the autocorrelation of the infection state of each node and the fraction of infected nodes both in
Liu, Q. (author) +1 more
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MathematicsControl chart pattern recognition was initially focused on single patterns with the assumption of normal, independent, and identical distribution.
Cang Wu +5 more
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Production, 2003 Este artigo apresenta procedimentos inferenciais para construir intervalos de confiança em índices de capacidade Cp e Cpk através de técnicas de reamostragem (bootstrap) quando os dados provenientes de processos normais são autocorrelacionados.This paper
Alberto W. Ramos, Linda Lee Ho
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Bayesian Cramér-Rao Lower Bounds for Prediction and Smoothing of Nonlinear TASD Systems
Sensors, 2022 The performance evaluation of state estimators for nonlinear regular systems, in which the current measurement only depends on the current state directly, has been widely studied using the Bayesian Cramér-Rao lower bound (BCRLB).
Xianqing Li +3 more
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