Raoul Ppp Grasman
|[This author has chosen not to make the email address public]|
Universiteit van Amsterdam (University of Amsterdam)http://www.uva.nl
Research outputJump to: Articles
- Peter Halpin & Conor Dolan & Raoul Grasman & Paul Boeck, 2011. "On the Relation Between the Linear Factor Model and the Latent Profile Model," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 564-583, October.
- Wetzels, Ruud & Grasman, Raoul P.P.P. & Wagenmakers, Eric-Jan, 2010. "An encompassing prior generalization of the Savage-Dickey density ratio," Computational Statistics & Data Analysis, Elsevier, vol. 54(9), pages 2094-2102, September.
CitationsMany of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.
- Wetzels, Ruud & Grasman, Raoul P.P.P. & Wagenmakers, Eric-Jan, 2010.
"An encompassing prior generalization of the Savage-Dickey density ratio,"
Computational Statistics & Data Analysis,
Elsevier, vol. 54(9), pages 2094-2102, September.
- Guido Consonni & Roberta Paroli, 2017. "Objective Bayesian Comparison of Constrained Analysis of Variance Models," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 589-609, September.
- Michael D. Lee, 2015. "Evidence for and against a simple interpretation of the less-is-more effect," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(1), pages 18-33, January.
- Oh, Man-Suk, 2014. "Bayesian comparison of models with inequality and equality constraints," Statistics & Probability Letters, Elsevier, vol. 84(C), pages 176-182.
- Bartolucci, Francesco & Scaccia, Luisa & Farcomeni, Alessio, 2012. "Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4067-4080.
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