Iterative Distributed Multinomial Regression
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917853365534720 |
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| author | Fan, Yanqin Okar, Yigit Shi, Xuetao |
| author_facet | Fan, Yanqin Okar, Yigit Shi, Xuetao |
| contents | This article introduces an iterative distributed computing estimator for the multinomial logistic regression model with large choice sets. Compared to the maximum likelihood estimator, the proposed iterative distributed estimator achieves significantly faster computation and, when initialized with a consistent estimator, attains asymptotic efficiency under a weak dominance condition. Additionally, we propose a parametric bootstrap inference procedure based on the iterative distributed estimator and establish its consistency. Extensive simulation studies validate the effectiveness of the proposed methods and highlight the computational efficiency of the iterative distributed estimator. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_01030 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Iterative Distributed Multinomial Regression Fan, Yanqin Okar, Yigit Shi, Xuetao Econometrics This article introduces an iterative distributed computing estimator for the multinomial logistic regression model with large choice sets. Compared to the maximum likelihood estimator, the proposed iterative distributed estimator achieves significantly faster computation and, when initialized with a consistent estimator, attains asymptotic efficiency under a weak dominance condition. Additionally, we propose a parametric bootstrap inference procedure based on the iterative distributed estimator and establish its consistency. Extensive simulation studies validate the effectiveness of the proposed methods and highlight the computational efficiency of the iterative distributed estimator. |
| title | Iterative Distributed Multinomial Regression |
| topic | Econometrics |
| url | https://arxiv.org/abs/2412.01030 |