A robust Bayesian approach to null intercept measurement error model with application to dental data
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Publication:961235
DOI10.1016/j.csda.2008.09.024zbMath1452.62809OpenAlexW2085050441MaRDI QIDQ961235
Pulak Ghosh, Cristian L. Bayes, Victor Hugo Lachos
Publication date: 30 March 2010
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2008.09.024
Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)
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- Inference from iterative simulation using multiple sequences
- Null intercept measurement error regression models
- Monte Carlo methods in Bayesian computation
- A Bayesian \(\chi^2\) test for goodness-of-fit
- The multivariate skew-slash distribution
- Robust Likelihood Methods Based on the Skew-t and Related Distributions
- Bayesian analysis for a skew extension of the multivariate null intercept measurement error model
- Sampling-Based Approaches to Calculating Marginal Densities
- Bayesian analysis of null intercept errors-in-variables regression for pretest/post-test data
- Local influence in null intercept measurement error regression under a student_t model
- APPLICATION OF GENERALIZED ESTIMATING EQUATIONS TO A DENTAL RANDOMIZED CLINICAL TRIAL
- Statistical Applications of the Multivariate Skew Normal Distribution
- The multivariate skew-normal distribution
- Bayesian Robust Multivariate Linear Regression With Incomplete Data
- Multivariate skewt-distribution
- Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skewt-Distribution
- Bayesian Measures of Model Complexity and Fit
- Likelihood-Based Inference for Multivariate Skew-Normal Regression Models
- A general class of multivariate skew-elliptical distributions
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