Stein EWMA Control Charts for Count Processes
Fuente:
arXiv
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909078954967040 |
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| author | Weiß, Christian H. |
| author_facet | Weiß, Christian H. |
| contents | The monitoring of serially independent or autocorrelated count processes is considered, having a Poisson or (negative) binomial marginal distribution under in-control conditions. Utilizing the corresponding Stein identities, exponentially weighted moving-average (EWMA) control charts are constructed, which can be flexibly adapted to uncover zero inflation, over- or underdispersion. The proposed Stein EWMA charts' performance is investigated by simulations, and their usefulness is demonstrated by a real-world data example from health surveillance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_11789 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Stein EWMA Control Charts for Count Processes Weiß, Christian H. Methodology The monitoring of serially independent or autocorrelated count processes is considered, having a Poisson or (negative) binomial marginal distribution under in-control conditions. Utilizing the corresponding Stein identities, exponentially weighted moving-average (EWMA) control charts are constructed, which can be flexibly adapted to uncover zero inflation, over- or underdispersion. The proposed Stein EWMA charts' performance is investigated by simulations, and their usefulness is demonstrated by a real-world data example from health surveillance. |
| title | Stein EWMA Control Charts for Count Processes |
| topic | Methodology |
| url | https://arxiv.org/abs/2401.11789 |