Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy-Reference-Cited by-同舟云学术

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Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy

Published:2023-01-01 Issue:none Volume:17 Page:
ISSN:1935-7516
Container-title:Statistics Surveys
language:
Short-container-title:Statist. Surv.

Author:

Bürkner Paul-Christian¹,Scholz Maximilian²,Radev Stefan T.³

Affiliation:

1. Department of Statistics, TU Dortmund University, Germany; Cluster of Excellence SimTech, University of Stuttgart, Germany

2. Cluster of Excellence SimTech, University of Stuttgart, Germany

3. Cluster of Excellence STRUCTURES, University of Heidelberg, Germany; Cognitive Science Department, Rensselaer Polytechnic Institute, NY, USA

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference326 articles.

1. Nelder, J. A. and Wedderburn, R. W. (1972). Generalized linear models. Journal of the Royal Statistical Society: Series A (General) 135 370–384.

2. IMBENS, G. W. and RUBIN, D. B. (2015). Causal inference in statistics, social, and biomedical sciences. Cambridge University Press.

3. CHEN, H., CHEN, J. and KALBFLEISCH, J. D. (2004). Testing for a finite mixture model with two components. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 66 95–115.

4. BLEI, D. M., KUCUKELBIR, A. and MCAULIFFE, J. D. (2017). Variational inference: a review for statisticians. Journal of the American Statistical Association 112 859–877.

5. BLEI, D. M., KUCUKELBIR, A. and MCAULIFFE, J. D. (2017). Variational inference: a review for statisticians. Journal of the American Statistical Association 112 859–877.

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