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中文摘要：
为了解决多元自相关过程的残差T^2控制图对小偏移不灵敏的问题，本文利用批量-均值法的思想，结合VAR模型的渐近分布，设计了多元自相关过程的向量自回归（VAR）控制图。只要子组样本量足够大，VAR控制图可以对过程出现的各种偏移进行有效控制。通过对比残差T^2控制图的控制效果，得出VAR控制图对小偏移灵敏、残差T^2控制图对大偏移灵敏的结论，联合使用VAR控制图和残差T^2控制图可更有效地监控多元自相关过程。
英文摘要：
Residual-based T^2 control chart is not effective for monitoring the multivariate autocorrelated processes with shifts extremely small. In this paper, based on the thinking of batch-means, a control procedure is provided using the methodological conclusion of distribution characteristics for vector autoregressive model （VAR）, termed the VAR control scheme. As long as subgroup size is sufficient large, VAR control scheme can be used efficiently to monitor all shifts, even extremely small. Compared with residual-based T^2 control chart, VAR control scheme is sensitive for small shifts and residual-based T^2 control chart is sensitive for big shifts comparatively. Thus it is more effective to monitoring the multivariate autocorrelated observations by combining VAR control scheme and residual T^2 control chart.
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