Likelihood analysis for a class of beta mixed models

DOI10.1080/02664763.2014.947248OpenAlexW3106391384MaRDI QIDQ5130143

Paulo J. jun. Ribeiro, Walmes Marques Zeviani, Wagner Hugo Bonat

Publication date: 4 November 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1312.2413

zbMATH Keywords

Laplace approximationlikelihood inferencewater qualityhierarchical modelslife qualitydata-cloning

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (16)

Unnamed Item ⋮ Unnamed Item ⋮ Unit gamma mixed regression models for continuous bounded data ⋮ Quasi-beta longitudinal regression model applied to water quality index data ⋮ A new mixed‐effects regression model for the analysis of zero‐modified hierarchical count data ⋮ Unit gamma regression models for correlated bounded data ⋮ Efficient MCMC estimation of inflated beta regression models ⋮ A fast look-up method for Bayesian mean-parameterised Conway-Maxwell-Poisson regression models ⋮ Partially linear beta regression model with autoregressive errors ⋮ Empirical performance of estimation methods in beta mixed models with application to ecological data ⋮ Flexible quasi-beta regression models for continuous bounded data ⋮ Properties of the beta regression model for small area estimation of proportions and application to estimation of poverty rates ⋮ Bayesian beta regression with Bayesianbetareg R-package ⋮ Beta rectangular regression models to longitudinal data ⋮ Unit-Lindley mixed-effect model for proportion data ⋮ A model-based approach to Spotify data analysis: a Beta GLMM

Uses Software

• R
• LBFGS-B
• JAGS
• betareg
• dclone

Cites Work

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• Unnamed Item
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• Estimability and Likelihood Inference for Generalized Linear Mixed Models Using Data Cloning
• BAYESIAN BETA REGRESSION: APPLICATIONS TO HOUSEHOLD EXPENDITURE DATA AND GENETIC DISTANCE BETWEEN FOOT‐AND‐MOUTH DISEASE VIRUSES
• Regression analysis of variates observed on (0, 1): percentages, proportions and fractions

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