The Pearson residual-based control charts for monitoring overdispersed count sequences
學年 114
學期 1
出版（發表）日期 2025-10-07
作品名稱 The Pearson residual-based control charts for monitoring overdispersed count sequences
作品名稱（其他語言）
著者 Zhengcheng Mou; Jyun-You Chiang; Tzong-Ru Tsai; Guojun Liu
單位
出版者
著錄名稱、卷期、頁數 Quality and Reliability Engineering International 42(1), p.461-477
摘要 Most existing control charts are designed for positively autocorrelated count data and seldom address the issue of overdispersion. The log-linear Poisson autoregression model (LLPAM) can capture overdispersion in count data, accommodate both positive and negative autocorrelations, and incorporate real-valued covariates. This makes it a more flexible alternative to the standard Poisson model. However, Shewhart-type charts applied to LLPAM often exhibit inflated false alarm rates and reduced sensitivity to parameter shifts under moderate temporal dependence. To address these limitations, we propose two monitoring schemes based on Pearson residuals (PRs): a Shewhart-type chart and an exponentially weighted moving average (EWMA) chart. Both methods allow simultaneous monitoring of LLPAM parameters under positive or negative autocorrelation. Simulation studies show that the proposed PR-based charts consistently outperform the observation-based Shewhart chart in terms of average run length (ARL), standard deviation of run length (SDRL), median run length (MDRL), and relative mean index (RMI), while maintaining false alarm rates close to nominal levels. An application to Escherichia coli infection data from North Rhine–Westphalia further demonstrates the practical utility of the proposed control charts.
關鍵字
語言 en_US
ISSN
期刊性質 國外
收錄於 SCI Scopus
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版
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機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/128424 )