On Some Aspects of Unbiased Estimation of Parameters in Quasi-Binomial Distributions

Sinha, Bikas K.; Das, Kishore Kumar; Mukhoti, Sujay

doi:10.1080/03610920802162706

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…A short account of such application concludes the paper. Further relevant results related to the main topic can be found in Bhat and Kulkarni (1966) regarding efficient multinomial sampling plans, in Sinha and Sinha (1992) for a review of the binomial case and in Sinha et al (2008) for generalizations to the quasi-binomial context.…”

Section: Introductionmentioning

confidence: 99%

Boundary Crossing Random Walks, Clinical Trials, and Multinomial Sequential Estimation

Bibbona

Rubba

2012

Sequential Analysis

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A sufficient condition for the uniqueness of multinomial sequential unbiased estimators is provided generalizing a classical result for binomial samples. Unbiased estimators are applied to infer the parameters of multidimensional or multinomial random walks that are observed until they reach a boundary. Clinical trials are shown to be representable within this scheme and an application to the estimation of the multinomial probabilities following multinomial clinical trials is presented.

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Section: Introductionmentioning

confidence: 99%

Boundary Crossing Random Walks, Clinical Trials, and Multinomial Sequential Estimation

Bibbona

Rubba

2012

Sequential Analysis

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Modeling under or over-dispersed binomial count data by using extended Altham distribution families

Asma

2021

Hacettepe Journal of Mathematics and Statistics

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While aiming particularly at handling under-dispersion, we explore a type of models constructed conservatively using the minimum information of first two moments for the fitting of binomial count data, which could have under, equal or over-dispersion. The extended Altham distribution (EAD) families were presented in this study. The extended Altham families are very close to the binomial distribution under equal dispersion setting, implying that they are alternative models of the binomial distribution. The feature that extended Altham families can reach the full range of dispersion outperforms some commonly used models such as extended beta-binomial and quasi-binomial which have restricted ranges of dispersion. Moreover, the extended Altham family can have double peaks at two boundaries, indicating they are feasible for fitting the double tail inflation phenomenon. This study illustrated the modeling using extended Altham families for both under-dispersed and over-dispersed binomial data resulted from disease cases within the same family.

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On Some Aspects of Unbiased Estimation of Parameters in Quasi-Binomial Distributions

Cited by 2 publications

References 19 publications

Boundary Crossing Random Walks, Clinical Trials, and Multinomial Sequential Estimation

Boundary Crossing Random Walks, Clinical Trials, and Multinomial Sequential Estimation

Modeling under or over-dispersed binomial count data by using extended Altham distribution families

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