Analyzing quantitative trait loci for the Arabidopsis Thaliana using Markov chain Monte Carlo model composition with restricted and unrestricted model spaces
DOI10.1016/j.stamet.2005.09.009zbMath1248.92025OpenAlexW2036162015MaRDI QIDQ713688
Keying Ye, Ann E. Stapleton, Edward L. Boone, Susan J. Simmons
Publication date: 19 October 2012
Published in: Statistical Methodology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.stamet.2005.09.009
Applications of statistics to biology and medical sciences; meta analysis (62P10) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40) Genetics and epigenetics (92D10)
Related Items (2)
Cites Work
- Unnamed Item
- Assessment of two approximation methods for computing posterior model probabilities
- Estimating the dimension of a model
- Bayesian model averaging: A tutorial. (with comments and a rejoinder).
- Accurate Approximations for Posterior Moments and Marginal Densities
- Approximate Bayes factors and accounting for model uncertainty in generalised linear models
- Bayesian Model Averaging for Linear Regression Models
- A Model Selection Approach for the Identification of Quantitative Trait Loci in Experimental Crosses
- Bayes Factors
- Bayesian Graphical Models for Discrete Data
- A Reference Bayesian Test for Nested Hypotheses and its Relationship to the Schwarz Criterion
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