Results 51 to 60 of about 575,579 (175)
, 2013 The effects of different parametrizations on the convergence of Bayesian computational algorithms for hierarchical models are well explored. Techniques such as centering, noncentering and partial noncentering can be used to accelerate convergence in MCMC
Nott, David J., Tan, Linda S. L.
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A stochastic variational framework for fitting and diagnosing generalized linear mixed models
, 2014 In stochastic variational inference, the variational Bayes objective function is optimized using stochastic gradient approximation, where gradients computed on small random subsets of data are used to approximate the true gradient over the whole data set.
Nott, David J., Tan, Linda S. L.
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Analysis of neonatal clinical trials with twin births
BMC Medical Research Methodology, 2009 Background In neonatal trials of pre-term or low-birth-weight infants, twins may represent 10–20% of the study sample. Mixed-effects models and generalized estimating equations are common approaches for handling correlated continuous or binary data ...
Shaffer Michele L +2 more
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Analysis of Fluid Velocity inside an Agricultural Sprayer Using Generalized Linear Mixed Models
Applied Sciences, 2020 The fluid velocity inside the tank of agricultural sprayers is an indicator of the quality of the mixture. This study aims to formulate the best generalized linear mixed model to infer the fluid velocity inside a tank under specific operational ...
Ángel Javier Aguirre +6 more
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Fitting Generalized Linear Mixed Models For Point-Referenced Spatial Data [PDF]
, 2003 Non-Gaussian point-referenced spatial data are frequently modeled using generalized linear mixed models (GLMM) with location-specific random effects. Spatial dependence can be introduced in the covariance matrix of the random effects.
Gemperli, Armin, Vounatsou, Penelope
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BMC Bioinformatics, 2020 Background Power analysis becomes an inevitable step in experimental design of current biomedical research. Complex designs allowing diverse correlation structures are commonly used in RNA-Seq experiments.
Lianbo Yu, Soledad Fernandez, Guy Brock
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Spatial variability in floodplain sedimentation: the use of generalized linear mixed-effects models [PDF]
Hydrology and Earth System Sciences, 2010 Sediment, Total Organic Carbon (TOC) and total nitrogen (TN) accumulation during one overbank flood (1.15 y return interval) were examined at one reach of the Middle Ebro River (NE Spain) for elucidating spatial patterns. To achieve this goal, four areas
A. Cabezas +4 more
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Global and local distance-based generalized linear models [PDF]
, 2016 This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models first to the generalized linear model framework. Then, a nonparametric version of these models is proposed by means of local
Boj, Eva +4 more
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Testing for misspecification in generalized linear mixed models [PDF]
Biostatistics, 2010 Generalized linear mixed models have become a frequently used tool for the analysis of non-Gaussian longitudinal data. Estimation is often based on maximum likelihood theory, which assumes that the underlying probability model is correctly specified.
Alonso Abad, Ariel +2 more
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The subset argument and consistency of MLE in GLMM: Answer to an open problem and beyond [PDF]
, 2013 We give answer to an open problem regarding consistency of the maximum likelihood estimators (MLEs) in generalized linear mixed models (GLMMs) involving crossed random effects.
Jiang, Jiming
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