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Bayesian outlier analysis in binary regression
(Routledge Journals, Taylor & Francis Ltd, 2010-01-01)
We propose alternative approaches to analyze residuals in binary regression models based on random effect components. Our preferred model does not depend upon any tuning parameter, being completely automatic. Although the ...
Bayesian outlier analysis in binary regression
(Routledge Journals, Taylor & Francis Ltd, 2010-01-01)
We propose alternative approaches to analyze residuals in binary regression models based on random effect components. Our preferred model does not depend upon any tuning parameter, being completely automatic. Although the ...
Bayesian outlier analysis in binary regression
(Routledge Journals, Taylor & Francis Ltd, 2014)
Effect of residual variance heterocedasticity on milk yield and age at first calving genetic parameter estimates
(2010-01-01)
Genetic evaluation programs assumed homocedasticity of residual variance estimates for different milk yield levels. The objective of this study was to estimate genetic parameters for 305-d milk yield (MY305) and age at ...
Bayesian longitudinal data analysis with mixed models and thick-tailed distributions using MCMC
(Carfax Publishing, 2004-08-01)
Linear mixed effects models are frequently used to analyse longitudinal data, due to their flexibility in modelling the covariance structure between and within observations. Further, it is easy to deal with unbalanced data, ...
Bayesian inference and diagnostics in zero-inflated generalized power series regression model
(Taylor & Francis Inc, 2016-01-01)
The paper provides a Bayesian analysis for the zero-inflated regression models based on the generalized power series distribution. The approach is based on Markov chain Monte Carlo methods. The residual analysis is discussed ...
Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation
(2003-01-01)
Linear mixed effects models have been widely used in analysis of data where responses are clustered around some random effects, so it is not reasonable to assume independence between observations in the same cluster. In ...
Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation
(2003-01-01)
Linear mixed effects models have been widely used in analysis of data where responses are clustered around some random effects, so it is not reasonable to assume independence between observations in the same cluster. In ...
A Bayesian generalized multiple group IRT model with model-fit assessment tools
(Elsevier Science BvAmsterdamHolanda, 2012)