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Linear contrasts for the one way analysis of variance: A Bayesian approach

Author

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  • Cano, J.A.
  • Carazo, C.
  • Salmerón, D.

Abstract

Linear contrasts between means for the one way analysis of variance are studied for the first time as objective model selection problems. For it, Bayes factors for intrinsic priors are used and classical and Bayesian measures of evidence are compared.

Suggested Citation

  • Cano, J.A. & Carazo, C. & Salmerón, D., 2016. "Linear contrasts for the one way analysis of variance: A Bayesian approach," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 54-62.
    • Handle: RePEc:eee:stapro:v:109:y:2016:i:c:p:54-62
    DOI: 10.1016/j.spl.2015.11.001
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    References listed on IDEAS

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    1. F. Javier Girón & M. Lina Martínez & Elías Moreno & Francisco Torres, 2006. "Objective Testing Procedures in Linear Models: Calibration of the p‐values," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(4), pages 765-784, December.
    2. J. Cano & C. Carazo & D. Salmerón, 2013. "Bayesian model selection approach to the one way analysis of variance under homoscedasticity," Computational Statistics, Springer, vol. 28(3), pages 919-931, June.
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    Cited by:

    1. J. A. Cano & C. Carazo & D. Salmerón, 2018. "Objective Bayesian model selection approach to the two way analysis of variance," Computational Statistics, Springer, vol. 33(1), pages 235-248, March.

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