@book{gelman:bayesian:2003,
	abstract = {{Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include: \&\#183;Stronger focus on MCMC\&\#183;Revision of the computational advice in Part III\&\#183;New chapters on nonlinear models and decision analysis\&\#183;Several additional applied examples from the authors' recent research\&\#183;Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more\&\#183;Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.}},
	author = {Gelman, Andrew   and Carlin, John  B.  and Stern, Hal  S.  and Rubin, Donald  B. },
	citeulike-article-id = {105949},
	howpublished = {Hardcover},
	isbn = {158488388X},
	keywords = {bayes, econometrics},
	month = {July},
	priority = {2},
	publisher = {{Chapman \& Hall/CRC}},
	title = {Bayesian Data Analysis, Second Edition},
	address = {Boca Ratón, FL},
	year = {2003}
}

@book{gelman:hill:2006,
	abstract = {{Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.}},
	author = {Gelman, Andrew   and Hill, Jennifer  },
	citeulike-article-id = {1068847},
	howpublished = {Hardcover},
	isbn = {0521867061},
	keywords = {r, regression, statistics},
	month = {December},
	priority = {4},
	publisher = {{Cambridge University Press}},
	address = {Cambridge},
	title = {Data Analysis Using Regression and Multilevel/Hierarchical Models},
	year = {2006}
}


@incollection{geweke:1992,
	author = {John F. Geweke},
	title = {Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments},
	year = {1992},
	editor = {J.O. Berger and J.M. Bernardo and A.P. Dawid and A.F.M. Smith},
	booktitle = {Bayesian Statistics 4},
	publisher = {Clarendon Press},
	address = {Oxford, UK}
}


@Manual{jags,
	title = {JAGS: Just Another Gibbs Sampler},
	author = {Martyn Plummer},
	year = {2013},
  url = {https://mcmc-jags.sourceforge.io/},
  note = {Version 3.4.0}
}
@misc{stan,
  author = {{Stan Development Team}},
  year = 2013,
  title = {\proglang{Stan}: A C++ Library for Probability and Sampling, Version 1.3},
  url = {https://mc-stan.org/}
}

@Manual{R,
  title = {\proglang{R}: A Language and Environment for Statistical Computing},
  author = {{R Core Team}},
  organization = {R Foundation for Statistical Computing},
  address = {Vienna, Austria},
  year = {2015},
  url = {http://www.R-project.org},
}

@article{coda,
  title = {\pkg{CODA}: Convergence Diagnosis and Output Analysis for MCMC},
  author = {Martyn Plummer and Nicky Best and Kate Cowles and Karen Vines},
  journal = {R News},
  year = {2006},
  volume = {6},
  number = {1},
  pages = {7--11},
  url = {http://CRAN.R-project.org/doc/Rnews/},
  pdf = {http://CRAN.R-project.org/doc/Rnews/Rnews_2006-1.pdf},
} 


@Article{boa,
  title = {\pkg{boa}: An {R} {P}ackage for {MCMC} Output Convergence Assessment and Posterior Inference},
  author = {Brian J. Smith},
  year = {2007},
  journal = {Journal of Statistical Software},
  volume = {21},
  number = {11},
  pages = {1--37},
}

@book{wilkinson:2005:grammar,
  title={The Grammar of Graphics},
  author={Wilkinson, L. and Wills, D. and Rope, D. and Norton, A. and Dubbs, R.},
  isbn={9780387245447},
  lccn={05043230},
  series={Statistics and Computing},
  year={2005},
  publisher={Springer-Verlag}
}

@book{wickham:2009:ggplot2,
  title={\pkg{ggplot2}: Elegant Graphics for Data Analysis},
  author={Wickham, Hadley},
  isbn={9780387981406},
  lccn={2009928510},
  series={Use R!},
  year={2009},
  url={https://books.google.es/books?id=bes-AAAAQBAJ},
  publisher={Springer-Verlag}
}


@article{greenhill:2011:separation,
  title={The Separation Plot: a New Visual Method for Evaluating the Fit of Binary Models},
  author={Greenhill, Brian and Ward, Michael D and Sacks, Audrey},
  journal={American Journal of Political Science},
  volume={55},
  number={4},
  pages={991--1002},
  year={2011},
  publisher={Wiley Online Library}
}

@Article{mcmcpack,
  title = {{\pkg{MCMCpack}}: Markov Chain Monte Carlo in {\proglang{R}}},
  author = {Andrew D. Martin and Kevin M. Quinn and Jong Hee Park},
  journal = {Journal of Statistical Software},
  year = {2011},
  volume = {42},
  number = {9},
  pages = {22},
  url = {https://www.jstatsoft.org/article/view/v042i09},
}
@article{wickham:2014:tidy,
  title={Tidy data},
  author={Wickham, Hadley},
  journal={Under review},
  year={2014}
}

@book{tufte:1983:visual,
  title={The visual display of quantitative information},
  author={Tufte, Edward R and Graves-Morris, PR},
  volume={2},
  year={1983},
  publisher={Graphics press Cheshire, CT}
}

@Manual{brms,
  title = {\pkg{brms}: Bayesian Regression Models Using \pkg{Stan}},
  author = {Paul-Christian Buerkner},
  year = {2016},
  note = {\proglang{R} package version 0.9.0},
  url = {https://CRAN.R-project.org/package=brms},
}


@Misc{rstanarm,
  title = {rstanarm: {Bayesian} applied regression modeling via {Stan}.},
  author = {Ben Goodrich and Jonah Gabry and Imad Ali and Sam Brilleman},
  note = {R package version 2.17.4},
  year = {2018},
  url = {https://mc-stan.org/},
}
