Multivariate zero-inflated Poisson models and their applications
Multivariate zero-inflated Poisson models and their applications
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DOI：
10.2307/1270992
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发表时间：
1999-02-01
期刊：
影响因子：
2.5
通讯作者：
Park, JH
中科院分区：
文献类型：
--
作者：
Li, CS;Lu, JC;Park, JH
零膨胀泊松（ZIP）分布已被证明是有用的制造过程中产生大量的无缺陷产品的建模结果。当存在多种类型的缺陷时，多变量ZIP（MZIP）模型可用于检测特定工艺设备问题并同时减少多种类型的缺陷。本文提出了MZIP模型的类型，并研究了MZIP模型的分布特性。小样本仿真研究表明，与矩量法相比，极大似然法在估计模型参数时具有更小的偏差和方差，以及更准确的覆盖概率和零缺陷概率。现实生活中的例子，从一个主要的电子设备制造商说明所提出的程序是如何有用的设备故障检测和协变量效应研究的制造环境。
The zero-inflated Poisson (ZIP) distribution has been shown to be useful for modeling outcomes of manufacturing processes producing numerous defect-free products. When there are several types of defects, the multivariate ZIP (MZIP) model can be useful to detect specific process equipment problems and to reduce multiple types of defects simultaneously. This article proposes types of MZIP models and investigates distributional properties of an MZIP model. Finite-sample simulation studies show that, compared to the method of moments, the maximum likelihood method has smaller bias and variance, as well as more accurate coverage probability in estimating model parameters and zero-defect probability. Real-life examples from a major electronic equipment manufacturer illustrate how the proposed procedures are useful in a manufacturing environment for equipment-fault detection and for covariate effect studies.