Process Capability Cp Assessment for Auto-Correlated Data in the Presence of Measurement Errors

Pub Date : 2022-11-16 DOI:10.1142/s0218539322500103
M. Z. Anis, Kuntal Bera
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引用次数: 1

Abstract

In this paper, we shall discuss some statistical properties of the estimator of [Formula: see text] when sample observations are autocorrelated and affected by measurement errors. The presence of autocorrelation in production units is very common in many industries like chemical, food processing, pharmaceutical, paper, and mineral. At the same time some amount of measurement error is invariably present in the sample observations due to inaccurate measurement process. In this paper, we discuss the case of a first-order stationary autoregressive process where measurement error follows a Gaussian distribution. The comparison of the statistical properties of the estimator in this case with the error-free case is the subject matter of this paper.
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存在测量误差的自相关数据过程能力Cp评价
本文讨论了样本观测值自相关且受测量误差影响时[公式:见文]估计量的一些统计性质。在化工、食品加工、制药、造纸和矿物等许多行业中,生产单位中存在自相关现象是非常普遍的。同时,由于测量过程不准确,在样品观测中总是存在一定的测量误差。本文讨论了测量误差服从高斯分布的一阶平稳自回归过程。在这种情况下与无误差情况下估计量的统计性质的比较是本文的主题。
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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