Statistical inference for zero-and-one-inflated poisson models
In this paper, a zero-and-one-inflated Poisson (ZOIP) model is studied. The maximum likelihood estimation and the Bayesian estimation of the model parameters are obtained based on data augmentation method. A simulation study based on proposed sampling algorithm is conducted to assess the performance...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2017-07-01
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| Series: | Statistical Theory and Related Fields |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/24754269.2017.1400419 |
| Summary: | In this paper, a zero-and-one-inflated Poisson (ZOIP) model is studied. The maximum likelihood estimation and the Bayesian estimation of the model parameters are obtained based on data augmentation method. A simulation study based on proposed sampling algorithm is conducted to assess the performance of the proposed estimation for various sample sizes. Finally, two real data-sets are analysed to illustrate the practicability of the proposed method. |
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| ISSN: | 2475-4269 2475-4277 |