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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2407.12308 |
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| _version_ | 1866908536153309184 |
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| author | Muia, Mathias N. Longla, Martial |
| author_facet | Muia, Mathias N. Longla, Martial |
| contents | This paper examines the impact of discrete marginal distributions on copula-based Markov chains. We present results on mixing and parameter estimation for a copula-based Markov chain model with Bernoulli($p$) marginal distribution and highlight the differences between continuous and discrete state-space Markov chains. We derive estimators for model parameters using the maximum likelihood approach and discuss other estimators of $p$ that are asymptotically equivalent to its maximum likelihood estimator. The asymptotic distributions of the parameter estimators are provided. A simulation study showcases the performance of the different estimators of $p$. Additionally, statistical tests for model parameters are included. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_12308 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Point on Discrete versus Continuous State-Space Markov Chains Muia, Mathias N. Longla, Martial Statistics Theory This paper examines the impact of discrete marginal distributions on copula-based Markov chains. We present results on mixing and parameter estimation for a copula-based Markov chain model with Bernoulli($p$) marginal distribution and highlight the differences between continuous and discrete state-space Markov chains. We derive estimators for model parameters using the maximum likelihood approach and discuss other estimators of $p$ that are asymptotically equivalent to its maximum likelihood estimator. The asymptotic distributions of the parameter estimators are provided. A simulation study showcases the performance of the different estimators of $p$. Additionally, statistical tests for model parameters are included. |
| title | A Point on Discrete versus Continuous State-Space Markov Chains |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2407.12308 |