The influence of parameter estimation on the ARL of Shewhart type charts for time series

DOI10.1007/BF02926102zbMath0948.62083OpenAlexW1982732343MaRDI QIDQ1567078

Wolfgang Schmid, Holger Kramer

Publication date: 16 November 2000

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02926102

zbMATH Keywords

time seriesstatistical process controlaverage run lengthcontrol schemesmodified control chartsresidual chartsShewhart 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 (11)

Properties and Use of the Shewhart Method and Its Followers ⋮ EWMA charts for monitoring the mean and the autocovariances of stationary processes ⋮ Parameter estimation for binomial \(\mathrm{AR}(1)\) models with applications in finance and industry ⋮ CUSUM charts for monitoring the mean of a multivariate Gaussian process ⋮ Control charts for high-dimensional time series with estimated in-control parameters ⋮ Control charts for time series ⋮ Surveillance of the covariance matrix based on the properties of the singular Wishart distribution ⋮ Robust surveillance of covariance matrices using a single observation ⋮ Guaranteed conditional ARL performance in the presence of autocorrelation ⋮ Effect of autocorrelation estimators on the performance of the X̄ control chart ⋮ Misleading Signals in Simultaneous Residual Schemes for the Mean and Variance of a Stationary Process

Cites Work

• The multivariate normal distribution
• Time series: theory and methods.
• Higher order asymptotic theory for time series analysis
• CUSUM control schemes for Gaussian processes
• On the run length of a Shewhart chart for correlated data
• Monitoring Processes That Wander Using Integrated Moving Average Models
• The effect of autocorrelation on the retrospectiveX-chart
• Control Charts in the Presence of Data Correlation
• Performance of CUSUM Control Schemes for Serially Correlated Observations
• Run-Length Distributions of Special-Cause Control Charts for Correlated Processes
• Ewma charts for multivariate time series
• An approach to the probability distribution of cusum run length
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