EWMA Charts for Monitoring the Mean and the Autocovariances of Stationary Gaussian Processes

DOI10.1081/SQA-120026884zbMath1029.62089MaRDI QIDQ4439627

M. Rosołowski, Wolfgang Schmid

Publication date: 14 December 2003

Published in: Sequential Analysis (Search for Journal in Brave)

zbMATH Keywords

time series analysisexponential smoothingstatistical process controlsimultaneous control charts

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics in engineering and industry; control charts (62P30)

Related Items (9)

On the misleading signals in simultaneous schemes for the mean vector and covariance matrix of multivariate i.i.d. output ⋮ Properties and Use of the Shewhart Method and Its Followers ⋮ EWMA Control Charts for Monitoring Optimal Portfolio Weights ⋮ EWMA charts for monitoring the mean and the autocovariances of stationary processes ⋮ Surveillance of the covariance matrix of multivariate nonlinear time series ⋮ Behavior of EWMA type control charts for small smoothing parameters ⋮ EWMA Charts for Multivariate Output: Some Stochastic Ordering Results ⋮ Optimal Sequential Surveillance for Finance, Public Health, and Other Areas ⋮ Optimal Surveillance Based on Exponentially Weighted Moving Averages

Cites Work

• Time series: theory and methods.
• CUSUM control schemes for Gaussian processes
• On the run length of a Shewhart chart for correlated data
• A Multivariate Exponentially Weighted Moving Average Control Chart
• Performance of CUSUM Control Schemes for Serially Correlated Observations
• SEQUENTIAL METHODS FOR DETECTING CHANGES IN THE VARIANCE OF ECONOMIC TIME SERIES
• Ewma charts for multivariate time series
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