| dc.contributor | 統計系 | |
| dc.creator (作者) | 楊素芬 | |
| dc.creator (作者) | Lu, Ming-Che;Yang, Su-Fen | |
| dc.date (日期) | 2026-06 | |
| dc.date.accessioned | 3-Sep-2026 09:21:12 (UTC+8) | - |
| dc.date.available | 3-Sep-2026 09:21:12 (UTC+8) | - |
| dc.date.issued (上傳時間) | 3-Sep-2026 09:21:12 (UTC+8) | - |
| dc.identifier.uri (URI) | https://ah.lib.nccu.edu.tw/item?item_id=184725 | - |
| dc.description.abstract (摘要) | Multivariate count data are often overdispersed due to additional sampling variability, such as clumped sampling (Efron, 1986). This study explores the statistical process control of multinomial distribution for overdispersed count data. Bayesian methods are used to construct multinomial control charts due to computational simplicity, ease of interpretation, and evidence in favor of in-control. Using the Dirichlet distribution as a prior, Bayesian exponentially weighted moving average (EWMA) control charts are proposed for monitoring the multinomial overdispersion process. The average run lengths (ARL) of the proposed control charts are calculated by Monte Carlo simulations to evaluate their detection performances. Moreover, the comparison results show that the proposed control charts present fewer false alarms than existing multinomial control charts which do not consider overdispersion. | |
| dc.format.extent | 572522 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | The 40th International Workshop on Statistical Modelling (IWSM2026), OSLO University | |
| dc.title (題名) | A Bayesian EWMA Control Chart for Monitoring Multinomial Overdispersion Processes | |
| dc.type (資料類型) | conference | |
