Results 11 to 20 of about 41,785 (303)
Clustering Algorithm for Zero-Inflated Data [PDF]
, 2020 Zero-inflated data are common in biomedical research. In cluster analysis, the heuristic approach fails to provide inferential properties to the outcome while the existing model-based approach only works in the case of a mixture of multivariate normal.
Thanataveerat, Anusorn
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Bayesian Copula Density Deconvolution for Zero-Inflated Data in Nutritional Epidemiology. [PDF]
J Am Stat Assoc, 2021 © 2020, © 2020 American Statistical Association. Estimating the marginal and joint densities of the long-term average intakes of different dietary components is an important problem in nutritional epidemiology.
Sarkar A +3 more
europepmc +4 more sources
Introducing COZIGAM: An R Package for Unconstrained and Constrained Zero-Inflated Generalized Additive Model Analysis [PDF]
Journal of Statistical Software, 2010 Zero-inflation problem is very common in ecological studies as well as other areas. Nonparametric regression with zero-inflated data may be studied via the zero-inflated generalized additive model (ZIGAM), which assumes that the zero-inflated responses ...
Hai Liu, Kung-Sik Chan
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Small Area Estimation on Zero-Inflated Data Using Frequentist and Bayesian Approach [PDF]
, 2020 The most commonly used method of small area estimation (SAE) is the empirical best linear unbiased prediction method based on a linear mixed model. However, it is not appropriate in the case of the zero-inflated target variable with a mixture of zeros ...
Aqmaliyah, Euis +2 more
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Trials, 2023 Background Two characteristics of commonly used outcomes in medical research are zero inflation and non-negative integers; examples include the number of hospital admissions or emergency department visits, where the majority of patients will have zero ...
Kyung Hyun Lee +4 more
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A score test for zero‐inflation in correlated count data [PDF]
Statistics in Medicine, 2005 AbstractTo account for the preponderance of zero counts and simultaneous correlation of observations, a class of zero‐inflated Poisson mixed regression models is applicable for accommodating the within‐cluster dependence. In this paper, a score test for zero‐inflation is developed for assessing correlated count data with excess zeros.
Xiang, Liming +3 more
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Justification for considering zero-inflated models in crash frequency analysis
Transportation Research Interdisciplinary Perspectives, 2020 One common challenge of modeling intersection related crash data is the high proportion of sites with zero crashes. Extensive research has been done on appropriate methods to handle excess zeroes.
Timo Pew +3 more
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Marginal Mean Models for Zero-Inflated Count Data [PDF]
Biometrics, 2016 Summary Zero-inflated regression models have emerged as a popular tool within the parametric framework to characterize count data with excess zeros. Despite their increasing popularity, much of the literature on real applications of these models has centered around the latent class formulation where the mean response of the so-called at ...
Todem, David +2 more
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Kendall's Tau for zero-inflated data [PDF]
, 2018 R code for a Kendall's tau correlation matrix calculator used for large datasets with zero-inflated data, such as genetic sequencing ...
Vincent G. Martinson (5041973) +6 more
core +1 more source
Predicting cyanobacteria abundance with Bayesian zero-inflated models
Journal of Hydroinformatics, 2023 Cyanobacterial blooms are a persistent concern to water management and treatment, with blooms potentially causing the release of toxins and degrading water quality.
Yirao Zhang, Nicolas M. Peleato
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