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Estimation of Fixed Parameters in Negative Binomial Mixed Model Using Shrinkage Estimators | ||
| Journal of Data Science and Modeling | ||
| دوره 1، شماره 2، اسفند 2021، صفحه 99-124 اصل مقاله (449.84 K) | ||
| نوع مقاله: Research Manuscript | ||
| شناسه دیجیتال (DOI): 10.22054/jcsm.2021.56488.1023 | ||
| نویسندگان | ||
Zahra Zandi؛ Hossein Bevrani؛ Reza Arabi Belaghi 
| ||
| Department of Statistics, University of Tabriz, Tabriz, Iran | ||
| چکیده | ||
| In this paper, we consider the problem of parameter estimation in {color{blue} negative binomial mixed model} when it is suspected that some of the fixed parameters may be restricted to a subspace via linear shrinkage, {color{blue} preliminary test}, shrinkage {color{blue} preliminary test}, shrinkage, and positive shrinkage estimators along with the unrestricted maximum likelihood and restricted estimators. The random effects are considered as nuisance parameters. We conduct a Monte Carlo simulation study to evaluate the performance of each estimator in the sense of simulated relative efficiency. The results of simulation study reveal that the proposed estimation strategies perform more better than {color{blue} the} maximum likelihood method. The proposed estimators are applied to a real dataset to appraise their performance. | ||
| کلیدواژه‌ها | ||
| Longitudinal Data؛ Monte Carlo Simulation؛ Negative Binomial Mixed Model؛ Over-dispersion؛ Shrinkage Estimators | ||
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آمار تعداد مشاهده مقاله: 127 تعداد دریافت فایل اصل مقاله: 94 |
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