Bernstein-type approximation using the beta-binomial distribution
Statistica, 2013 The Bernstein-type approximation using the beta-binomial distribution is proposed and studied. Both univariate and multivariate Bernstein-type approximations are studied. The uniform convergence and the degree of approximation are studied.
Andrea Pallini
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A Bimodal Extension of the Beta-Binomial Distribution with Applications [PDF]
AxiomsIn this paper, we propose an alternative distribution to model count data exhibiting uni/bimodality. It arises as a weighted version of the beta-binomial distribution, which is defined by a parametric weight function that admits up to two modes for the ...
Jimmy Reyes +4 more
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Empirical Bayesian analysis of paired high-throughput sequencing data with a beta-binomial distribution. [PDF]
BMC Bioinformatics, 2013 Pairing of samples arises naturally in many genomic experiments; for example, gene expression in tumour and normal tissue from the same patients. Methods for analysing high-throughput sequencing data from such experiments are required to identify differential expression, both within paired samples and between pairs under different experimental ...
Hardcastle TJ, Kelly KA.
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Applications of Beta Negative Binomial Distribution and Laguerre Polynomials on Ozaki Bi-Close-to-Convex Functions [PDF]
Axioms, 2022 In the present paper, due to beta negative binomial distribution series and Laguerre polynomials, we investigate a new family FΣ(δ,η,λ,θ;h) of normalized holomorphic and bi-univalent functions associated with Ozaki close-to-convex functions.
Isra Al-Shbeil +3 more
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Generalised score distribution: underdispersed continuation of the beta-binomial distribution [PDF]
Statistical Papers, 2023 AbstractConsider a class of discrete probability distributions with a limited support. A typical example of such support is some variant of a Likert scale, with a response mapped to either the $$\{1, 2, \ldots , 5\}$$ { 1 , 2 ,
Bogdan Ćmiel +3 more
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A non-uniform bound on binomial approximation to the beta binomial cumulative distribution function [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2019 This paper uses Stein’s method and the characterization of beta binomial random variable to determine a non-uniform bound for the distance between the beta binomial cumulative distribution function with parameters n N, 0 and 0 and the ...
Kanint Teerapabolarn, Khunakorn Sae-Jeng
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Unimodal Behavior of the Negative Beta Binomial Distribution [PDF]
Sigmae, 2015 Neste artigo apresenta-se um estudo sobre o comportamento da distribuição BetaBinomial Negativa em relação a sua moda. Aplica-se este estudo quando essa distribuição é dada através de uma distribuição hipergeométrica equivalente multiplicada pela verossimilhança cada distribuição Binomial Negativa.
Pedro Ferreira de Lima +2 more
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NEGATIVE BINOMIAL APPROXIMATION TO THE BETA BINOMIAL DISTRIBUTION [PDF]
International Journal of Pure and Apllied Mathematics, 2015 This paper determines a bound on the approximation of the beta binomial distribution with parameters n, andby a negative binomial distri- bution with parametersand + + +n . With this bound, it is indicated that the beta binomial distribution can be well approximated by the negative binomial distribution whenis large.
K. Teerapabolarn
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Statistical Inference of the Beta Binomial Exponential 2 Distribution with Application to Environmental Data [PDF]
Axioms, 2022 A new four-parameter lifetime distribution called the beta binomial exponential 2 (BBE2) distribution is proposed. Some mathematical features, including quantile function, moments, generating function and characteristic function, of the BBE2 distribution,
Osama H. Mahmoud Hassan +3 more
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The sampling distribution of the maximum likelihood estimators for the parameters of beta-binomial distribution [PDF]
International Mathematical Forum, 2013 Summary: Sampling distributions for the maximum likelihood estimators of the beta-binomial model are obtained numerically using approximate random numbers from the beta-binomial distribution. STATGRAPHICS package is used to obtain the best fitted distributions using chi-square and Kolmogorov-Smirnov tests.
Samia Salem, Wael S. Abu El Azm
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