Results 111 to 120 of about 9,896 (146)
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Jeffreys Prior for Negative Binomial and Zero Inflated Negative Binomial Distributions
Sankhya A, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Arnab Maity
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The Zero-inflated Negative Binomial-Exponential Distribution and Its Application
Lobachevskii Journal of Mathematics, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bodhisuwan, Rujira, Kehler, Adam
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Biometrics, 2001
Summary. Count data often show a higher incidence of zero counts than would be expected if the data were Poisson distributed. Zero‐inflated Poisson regression models are a useful class of models for such data, but parameter estimates may be seriously biased if the nonzero counts are overdispersed in relation to the Poisson distribution.
Martin Ridout
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Summary. Count data often show a higher incidence of zero counts than would be expected if the data were Poisson distributed. Zero‐inflated Poisson regression models are a useful class of models for such data, but parameter estimates may be seriously biased if the nonzero counts are overdispersed in relation to the Poisson distribution.
Martin Ridout
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A test for lack-of-fit of zero-inflated negative binomial models
Journal of Statistical Computation and Simulation, 2019When a count data set has excessive zero counts, nonzero counts are overdispersed, and the effect of a continuous covariate might be nonlinear, for analysis a semiparametric zero-inflated negative ...
Chin-Shang Li, Shen-Ming Lee
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The zero-inflated negative binomial multilevel model: demonstrated by a Brazilian dataset
International Journal of Mathematics in Operational Research, 2017Luiz Paulo Favero
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Zero-inflated non-central negative binomial distribution
Applied Mathematics-A Journal of Chinese Universities, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tian, Wei-zhong +2 more
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A new Stein estimator for the zero‐inflated negative binomial regression model
Concurrency and Computation: Practice and Experience, 2022AbstractThe Zero‐inflated negative binomial (ZINB) regression models are mainly applied for count data that shows over‐dispersion and extra zeros. Multicollinearity is considered to be a significant problem in the estimation of parameters in the ZINB regression model. Thus, in order to alleviate the serious effects of multicollinearity, a new estimator
Muhammad Nauman Akram +4 more
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ZERO-INFLATED NEGATIVE BINOMIAL-LINDLEY DISTRIBUTION AND ITS APPLICATION
Far East Journal of Theoretical Statistics, 2019Summary: There are increasingly many attempts made in expanding the classes of mixed and compound distributions, especially using Lindley distribution which gives the better fit for count data. Further, many researchers have shown a keen interest in generalizing the Lindley distribution.
Sakthivel, K. M., Rajitha, C. S.
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A New Zero-Inflated Negative Binomial Methodology for Latent Category Identification
Psychometrika, 2013We introduce a new statistical procedure for the identification of unobserved categories that vary between individuals and in which objects may span multiple categories. This procedure can be used to analyze data from a proposed sorting task in which individuals may simultaneously assign objects to multiple piles. The results of a synthetic example and
Blanchard, Simon J., Desarbo, Wayne S.
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Sampling plans for the zero‐inflated negative binomial distribution in the food industry
Quality and Reliability Engineering International, 2018AbstractIn this paper, we propose 3 new sampling plans, including resubmitted single sampling plan (RSSP), repetitive group sampling (RGS) plan, and multiple dependent state (MDS) sampling plan to study the zero‐inflated negative binomial distribution in microbiological food safety and quality assurance practices.
Fu-Kwun Wang, Shalemu Sharew Hailemariam
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