Ewma charts for multivariate time series
- 1 January 1997
- journal article
- research article
- Published by Taylor & Francis Ltd in Sequential Analysis
- Vol. 16 (2), 131-154
- https://doi.org/10.1080/07474949708836378
Abstract
In this paper a muIt,ivariat.e EWMA chart for time series is introduced. In principle, it is a generalization of the control scheme of Lowry et al. (I992) for multivarite indendent observations. The autocovariances of the EWMA recursion are derived for stationary multivariate time series. IYsing tllese reslllts a co11t.rol chart hased or1 t11 illt.ivariate EWMA recursion is proposed. For a multivariate autoregressive process of order 1, a sufficient. condition is given such that the in-control average run length (ARL) is invariant, withrespect to the covariance of the White Noise process. This scheme is compared with the MEWMA control chart of Lowry et al. (1992) applied to the residuals. By an extensive Monte carlo study the ARL of both charts are determined for several multivariate autoregressive processses.Keywords
This publication has 21 references indexed in Scilit:
- Run-Length Distributions of Special-Cause Control Charts for Correlated ProcessesTechnometrics, 1994
- Predicting Shifts in the Mean of a Multivariate Time Series Process: An Application in Predicting Business FailuresJournal of the American Statistical Association, 1993
- A Multivariate Exponentially Weighted Moving Average Control ChartTechnometrics, 1992
- Statistical process control procedures for correlated observationsThe Canadian Journal of Chemical Engineering, 1991
- Multivariate Quality Control Based on Regression-Adjusted VariablesTechnometrics, 1991
- Exponentially Weighted Moving Average Control Schemes: Properties and EnhancementsTechnometrics, 1990
- Time-Series Modeling for Statistical Process ControlJournal of Business & Economic Statistics, 1988
- A Note on Multivariate CUSUM ProceduresTechnometrics, 1987
- Multivariate CUSUM Quality-Control ProceduresTechnometrics, 1985
- Sequential Estimation of Expectations in the Presence of Trend2Australian Journal of Statistics, 1981