Results 21 to 30 of about 42,459 (144)
Asian Journal of Probability and Statistics, 2019 Count data often violate the assumptions of a normal distribution due to the fact that they are bounded by their lowest value which is zero. The Poison distribution is sometimes suggested but when the assumption of equal mean and variance is violated due to over-dispersion and presence of zeros we tend to look in the direction of other models.
R. A. Ipinyomi, M. I. Adarabioyo
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MODELLING ZERO-INFLATED OVER DISPERSED DENGUE DATA VIA ZERO-INFLATED POISSON INVERSE GAUSSIAN REGRESSION MODEL: A CASE STUDY OF BANGLADESH [PDF]
Acta Scientifica MalaysiaBangladesh has been noted for experiencing some of the most susceptible dengue outbreaks in Asia; the country’s location, dense population, and changing environment all play major roles in this.
Sukanta Chakraborty +1 more
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Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data. [PDF]
PLoS ONE, 2015 Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators.
Lizhen Xu +3 more
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Mathematics, 2022 This article presents the results of the implementation of a forecasting model, to predict the relief materials needed for assisting in decisions prior to natural disasters, thus filling a gap in the exploration of Generalized Linear Mixed Models (GLMM ...
Camila Pareja Yale +2 more
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Zero inflated negative binomial-generalized exponential distributionand its applications [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2014 In this paper, we propose a new zero inflated distribution, namely, the zero inflated negative binomial-generalized exponential (ZINB-GE) distribution. The new distribution is used for count data with extra zeros and is an alternative for data analysis
Sirinapa Aryuyuen +2 more
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Performance of the Ridge and Liu Estimators in the zero-inflated Bell Regression Model
Journal of Mathematics, 2022 The Poisson regression model is popularly used to model count data. However, the model suffers drawbacks when there is overdispersion—when the mean of the Poisson distribution is not the same as the variance.
Zakariya Yahya Algamal +3 more
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Defending Zero Inflation: All for Naught [PDF]
Quarterly Review, 1991 Economists and policymakers disagree on the lengths central banks should go in pursuit of price stability and, in fact, on exactly what price stability means. This essay advocates that central banks try to maintain stable price levels in their countries, and it argues that the benefits of achieving this objective are worth the transition costs.
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Bayesian clustering of multiple zero-inflated outcomes
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2023 Several applications involving counts present a large proportion of zeros (excess-of-zeros data). A popular model for such data is the hurdle model, which explicitly models the probability of a zero count, while assuming a sampling distribution on the positive integers. We consider data from multiple count processes. In this context, it is
Beatrice Franzolini +3 more
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Bayesian model selection reveals biological origins of zero inflation in single-cell transcriptomics
Genome Biology, 2020 Background Single-cell RNA sequencing is a powerful tool for characterizing cellular heterogeneity in gene expression. However, high variability and a large number of zero counts present challenges for analysis and interpretation.
Kwangbom Choi +3 more
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Journal of MathematicsIn this study, we propose a new zero-inflated regression model as an alternative to zero-inflated regression models, such as the zero-inflated Poisson, zero-inflated negative binomial, zero-inflated hurdle-Poisson, and zero-inflated hurdle negative ...
Caner Tanış +5 more
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