基于位置尺度CUSUM方法的向量自回归时间序列统计过程监测

IF 1.3 4区工程技术 Q4 ENGINEERING, INDUSTRIAL

Quality Engineering Pub Date : 2022-12-13 DOI:10.1080/08982112.2022.2156295

Sangjo Lee, Sangyeol Lee

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引用次数: 1

摘要

摘要在本研究中，我们使用基于残差的累积和（CUSUM）控制图设计了一种向量自回归（VAR）和结构VAR（SVAR）时间序列的监测方法。残差是用顺序观察的测试样本和从训练样本获得的参数估计来计算的。当使用1型误差概率方案时，控制极限是渐近确定的，但在我们的经验研究中也使用了平均游程长度（ARL）。对于SVAR时间序列，采用独立分量分析（ICA）方法。对我们的方法进行了仿真研究和实际数据分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Statistical process monitoring for vector autoregressive time series based on location-scale CUSUM method

Abstract In this study, we design a monitoring method for the vector autoregressive (VAR) and structural VAR (SVAR) time series using the residual-based cumulative sum (CUSUM) control chart. The residuals are calculated with a sequentially observed testing sample and the parameter estimates obtained from a training sample. Control limits are determined asymptotically when type 1 error probability scheme is used, but average run length (ARL) is also used in our empirical study. For the SVAR time series, independent component analysis (ICA) method is applied. A simulation study and real data analysis are conducted to evaluate our method.

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来源期刊

Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY

CiteScore

3.90

自引率

10.00%

发文量

审稿时长

>12 weeks

期刊介绍： Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed. You are invited to submit manuscripts and application experiences that explore: Experimental engineering design and analysis Measurement system analysis in engineering Engineering process modelling Product and process optimization in engineering Quality control and process monitoring in engineering Engineering regression Reliability in engineering Response surface methodology in engineering Robust engineering parameter design Six Sigma method enhancement in engineering Statistical engineering Engineering test and evaluation techniques.