Smoothed Dirichlet Distribution

Abstract When the cells are ordinal in the multinomial distribution, i.e., when cells have a natural ordering, guaranteeing that the borrowing information among neighboring cells makes sense conceptually. In this paper, we introduce a novel probability distribution for borrowing information among ne...

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Main Authors: Lahiru Wickramasinghe, Alexandre Leblanc, Saman Muthukumarana
Format: Article
Language:English
Published: Springer 2023-09-01
Series:Journal of Statistical Theory and Applications (JSTA)
Subjects:
Online Access:https://doi.org/10.1007/s44199-023-00062-8
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author Lahiru Wickramasinghe
Alexandre Leblanc
Saman Muthukumarana
author_facet Lahiru Wickramasinghe
Alexandre Leblanc
Saman Muthukumarana
author_sort Lahiru Wickramasinghe
collection DOAJ
description Abstract When the cells are ordinal in the multinomial distribution, i.e., when cells have a natural ordering, guaranteeing that the borrowing information among neighboring cells makes sense conceptually. In this paper, we introduce a novel probability distribution for borrowing information among neighboring cells in order to provide reliable estimates for cell probabilities. The proposed smoothed Dirichlet distribution forces the probabilities of neighboring cells to be closer to each other than under the standard Dirichlet distribution. Basic properties of the proposed distribution, including normalizing constant, moments, and marginal distributions, are developed. Sample generation of smoothed Dirichlet distribution is discussed using the acceptance-rejection algorithm. We demonstrate the performance of the proposed smoothed Dirichlet distribution using 2018 Major League Baseball (MLB) batters data.
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spelling doaj.art-ceede5ff4fb045e286d82751d1e0e23a2023-12-03T12:38:25ZengSpringerJournal of Statistical Theory and Applications (JSTA)2214-17662023-09-0122423726110.1007/s44199-023-00062-8Smoothed Dirichlet DistributionLahiru Wickramasinghe0Alexandre Leblanc1Saman Muthukumarana2Department of Mathematics and Statistics, University of WinnipegDepartment of Statistics, University of ManitobaDepartment of Statistics, University of ManitobaAbstract When the cells are ordinal in the multinomial distribution, i.e., when cells have a natural ordering, guaranteeing that the borrowing information among neighboring cells makes sense conceptually. In this paper, we introduce a novel probability distribution for borrowing information among neighboring cells in order to provide reliable estimates for cell probabilities. The proposed smoothed Dirichlet distribution forces the probabilities of neighboring cells to be closer to each other than under the standard Dirichlet distribution. Basic properties of the proposed distribution, including normalizing constant, moments, and marginal distributions, are developed. Sample generation of smoothed Dirichlet distribution is discussed using the acceptance-rejection algorithm. We demonstrate the performance of the proposed smoothed Dirichlet distribution using 2018 Major League Baseball (MLB) batters data.https://doi.org/10.1007/s44199-023-00062-8Dirichlet distributionMultinomial distribution, Bayesian
spellingShingle Lahiru Wickramasinghe
Alexandre Leblanc
Saman Muthukumarana
Smoothed Dirichlet Distribution
Journal of Statistical Theory and Applications (JSTA)
Dirichlet distribution
Multinomial distribution, Bayesian
title Smoothed Dirichlet Distribution
title_full Smoothed Dirichlet Distribution
title_fullStr Smoothed Dirichlet Distribution
title_full_unstemmed Smoothed Dirichlet Distribution
title_short Smoothed Dirichlet Distribution
title_sort smoothed dirichlet distribution
topic Dirichlet distribution
Multinomial distribution, Bayesian
url https://doi.org/10.1007/s44199-023-00062-8
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AT alexandreleblanc smootheddirichletdistribution
AT samanmuthukumarana smootheddirichletdistribution