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THE TRUNCATED NEGATIVE BINOMIAL DISTRIBUTION

Biometrika, 1955
(1920), Fisher (1941), Haldane (1941), Anscoinbe (1950) and Bliss & Fisher (1953), and is extensively used for the description of data too heterogeneous to be fitted by a Poisson distribution. Observed samples, however, may be truncated, in the sense that the number of individuals falling into the zero class cannot be determined.
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Exploring the determinants of renewable energy innovation considering the institutional factors: A negative binomial analysis

Technology in Society, 2021
Qing-long Shao
exaly

Normal Distribution Binomial Heritage

2012
Acquaintance with the normal distribution, tables of the normal distribution. Probabilistic paper. Sample means distribution and Monte Carlo simulation. Two theorems of de Moivre-Laplace. When does normal approximation fit binomial distribution data? [Heritage of F.Gauss and Marquis de Laplace]
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Binomial Distribution

2008
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Binomial Distribution

2016
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Binomial Distribution

2006
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Flood susceptibility mapping by ensemble evidential belief function and binomial logistic regression model on river basin of eastern India

Advances in Space Research, 2020
Indrajit Chowdhuri +2 more
exaly

Too many zeros and/or highly skewed? A tutorial on modelling health behaviour as count data with Poisson and negative binomial regression

Health Psychology and Behavioral Medicine, 2021
James A Green
exaly

Binomial Distribution

2015
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