Confidence Intervals Using Turing's Estimator: Simulations and Applications
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912281504251904 |
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| author | Chang, Jie Grabchak, Michael Zhang, Jialin |
| author_facet | Chang, Jie Grabchak, Michael Zhang, Jialin |
| contents | Turing's estimator allows one to estimate the probabilities of outcomes that either do not appear or only rarely appear in a given random sample. We perform a simulation study to understand the finite sample performance of several related confidence intervals (CIs) and introduce an approach for selecting the appropriate CI for a given sample. We give an application to the problem of authorship attribution and apply it to a dataset comprised of tweets from users on X (Twitter). Further, we derive several theoretical results about asymptotic normality and asymptotic Poissonity of Turing's estimator for two important discrete distributions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_14313 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Confidence Intervals Using Turing's Estimator: Simulations and Applications Chang, Jie Grabchak, Michael Zhang, Jialin Statistics Theory Applications Turing's estimator allows one to estimate the probabilities of outcomes that either do not appear or only rarely appear in a given random sample. We perform a simulation study to understand the finite sample performance of several related confidence intervals (CIs) and introduce an approach for selecting the appropriate CI for a given sample. We give an application to the problem of authorship attribution and apply it to a dataset comprised of tweets from users on X (Twitter). Further, we derive several theoretical results about asymptotic normality and asymptotic Poissonity of Turing's estimator for two important discrete distributions. |
| title | Confidence Intervals Using Turing's Estimator: Simulations and Applications |
| topic | Statistics Theory Applications |
| url | https://arxiv.org/abs/2503.14313 |