Accurate ARL computation for EWMA-S2 control charts
Statistics and Computing
An EWMA chart for monitoring the process standard deviation when parameters are estimated
Computational Statistics & Data Analysis
Computation of the ARL for CUSUM-S2 schemes
Computational Statistics & Data Analysis
Evaluation of the run-length distribution for a combined Shewhart-EWMA control chart
Statistics and Computing
A control chart based on likelihood ratio test for detecting patterned mean and variance shifts
Computational Statistics & Data Analysis
Using one EWMA chart to jointly monitor the process mean and variance
Computational Statistics
Adaptive EWMA procedures for monitoring processes subject to linear drifts
Computational Statistics & Data Analysis
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The exponentially weighted moving average chart of the squared deviation (EWMAS) is often applied for monitoring changes such as step shifts and linear drifts in process variation when no subgrouping is available. This paper analyzes the performance of the EWMAS chart under drifts in process variation. A fast and accurate algorithm based on the piecewise collocation method is presented for computing both the zero-state and steady-state average run lengths of the EWMAS chart. It is shown that the proposed method can provide accurate approximation results in both zero-state and steady-state cases. Some optimal design tables are also provided to facilitate the design of EWMAS charts in practice.