BayesX: Analysing Bayesian structured additive regression models [PDF]
, 2003 There has been much recent interest in Bayesian inference for generalized additive and related models. The increasing popularity of Bayesian methods for these and other model classes is mainly caused by the introduction of Markov chain Monte Carlo (MCMC)
Brezger, Andreas +2 more
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ANALYSIS OF DISCRETE DATA USING LINEAR REGRESSION
Ecosistemas y Recursos Agropecuarios, 2014 Maximum likelihood estimates are obtained for a linear regressio model where the dependent variable is a linear transformation of mutinomially distributed random variables.
Robert J. Flowers
doaj +1 more source
Bayesian Zero-Inflated Negative Binomial Regression Based on Pólya-Gamma Mixtures. [PDF]
Bayesian Anal, 2019 Motivated by a study examining spatiotemporal patterns in inpatient hospitalizations, we propose an efficient Bayesian approach for fitting zero-inflated negative binomial models.
Neelon B.
europepmc +2 more sources
Model justification and stratification for confounding of Chlamydia trachomatis disease
Letters in Biomathematics, 2019 This study involves statistical analysis of reported cases of sexually transmitted diseases (STDs) of Chlamydia infection in the United States. The data are collected from 2007 to 2016.
Sarada Ghosh, G. P. Samanta
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A Dynamical and Zero-Inflated Negative Binomial Regression Modelling of Malaria Incidence in Limpopo Province, South Africa. [PDF]
Int J Environ Res Public Health, 2019 Recent studies have considered the connections between malaria incidence and climate variables using mathematical and statistical models. Some of the statistical models focused on time series approach based on Box–Jenkins methodology or on dynamic model.
Abiodun GJ +6 more
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BMC Medical Research Methodology, 2022 Background Hospital length of stay (LOS) is a key indicator of hospital care management efficiency, cost of care, and hospital planning. Hospital LOS is often used as a measure of a post-medical procedure outcome, as a guide to the benefit of a treatment
Gustavo A. Fernandez +1 more
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PENANGANAN OVERDISPERSI PADA MODEL REGRESI POISSON MENGGUNAKAN MODEL REGRESI BINOMIAL NEGATIF
Media Statistika, 2011 Poisson regression is the most popular tool for modeling the relationship between a discrete data in the response variable and a set of predictors with continue, discrete, categoric or mix data.
Rio Tongaril Simarmata, Dwi Ispriyanti
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Using Zero-inflated Count Regression Models To Estimate The Fertility Of U. S. Women [PDF]
, 2003 In the modeling of count variables there is sometimes a preponderance of zero counts. This article concerns the estimation of Poisson regression models (PRM) and negative binomial regression models (NBRM) to predict the average number of children ever ...
McKibben, Sherry L. +1 more
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PEMODELAN DATA KEMATIAN BAYI DENGAN GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION
Media Statistika, 2016 Overdispersion phenomenon and the influence of location or spatial aspect on data are handled using Binomial Geographically Weighted Regression (GWNBR).
Riza F. Ramadhan, Robert Kurniawan
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Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study [PDF]
, 2019 Background: It is unclear whether weighted or unweighted regression is preferred in the analysis of data derived from respondent driven sampling. Our objective was to evaluate the validity of various regression models, with and without weights and with ...
Avery, Lisa +5 more
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