references.bib

@article{William1984,
author = { William S.   Cleveland  and  Robert   McGill },
title = {Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods},
journal = {Journal of the American Statistical Association},
volume = {79},
number = {387},
pages = {531-554},
year  = {1984},
publisher = {Taylor & Francis},
doi = {10.1080/01621459.1984.10478080},
URL = { https://www.tandfonline.com/doi/abs/10.1080/01621459.1984.10478080},
eprint = { https://www.tandfonline.com/doi/pdf/10.1080/01621459.1984.10478080},
}

@inproceedings{Heer2010,
	address = {New York, NY, USA},
	series = {{CHI} '10},
	title = {Crowdsourcing graphical perception: using mechanical turk to assess visualization design},
	isbn = {978-1-60558-929-9},
	shorttitle = {Crowdsourcing graphical perception},
	url = {https://doi.org/10.1145/1753326.1753357},
	doi = {10.1145/1753326.1753357},
	urldate = {2023-09-28},
	booktitle = {Proceedings of the {SIGCHI} {Conference} on {Human} {Factors} in {Computing} {Systems}},
	publisher = {Association for Computing Machinery},
	author = {Heer, Jeffrey and Bostock, Michael},
	month = apr,
	year = {2010},
	keywords = {crowdsourcing, evaluation, experimentation, graphical perception, information visualization, mechanical turk, user study},
	pages = {203--212},
}

@incollection{diaconis2011,
	title = {Theories of {Data} {Analysis}: {From} {Magical} {Thinking} {Through} {Classical} {Statistics}},
	copyright = {Copyright © 1985, 2006 John Wiley \& Sons, Inc. All rights reserved.},
	isbn = {978-1-118-15070-2},
	shorttitle = {Theories of {Data} {Analysis}},
	abstract = {This chapter contains sections titled: Intuitive Statistics— Some Inferential Problems Multiplicity— A Pervasive Problem Some Remedies Theories for Data Analysis Uses for Mathematics In Defense of Controlled Magical Thinking},
	booktitle = {Exploring {Data} {Tables}, {Trends}, and {Shapes}},
	publisher = {John Wiley \& Sons, Ltd},
	author = {Diaconis, Persi},
	year = {2011},
	doi = {10.1002/9781118150702.ch1},
	keywords = {controlled magical thinking, data analysis, data structure, intuitive statistics, multiplicity},
	pages = {1--36},
}

@article{ghahramani2015,
	title = {Probabilistic {Machine} {Learning} and {Artificial} {Intelligence}},
	volume = {521},
	copyright = {© 2015 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
	issn = {0028-0836},
	doi = {10.1038/nature14541},
	abstract = {How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.},
	number = {7553},
	journal = {Nature},
	author = {Ghahramani, Zoubin},
	month = may,
	year = {2015},
	keywords = {Computer science, Mathematics and computing, neuroscience},
	pages = {452--459},
}

@book{bessiere2013,
	address = {Boca Raton},
	edition = {1 edition},
	title = {Bayesian {Programming}},
	isbn = {978-1-4398-8032-6},
	publisher = {Chapman and Hall/CRC},
    url = {https://www.crcpress.com/Bayesian-Programming/Bessiere-Mazer-Ahuactzin-Mekhnacha/p/book/9781439880326},
	author = {Bessiere, Pierre and Mazer, Emmanuel and Ahuactzin, Juan Manuel and Mekhnacha, Kamel},
	month = dec,
	year = {2013},
}

@book{daniel2015,
	title = {Probabilistic {Programming}},
	author = {{Daniel Roy}},
    url = {http://probabilistic-programming.org},
	year = {2015},
}


@article{xarray_2017,
	title = {Xarray: {N}-{D} {Labeled} {Arrays} and {Datasets} in {Python}},
	volume = {5},
	issn = {2049-9647},
	shorttitle = {Xarray},
	doi = {10.5334/jors.148},
	number = {1},
	journal = {Journal of Open Research Software},
	author = {Hoyer, Stephan and Hamman, Joe},
	month = apr,
	year = {2017},
	keywords = {data analysis, data, data handling, multidimensional, netCDF, pandas, Python},
}

@article{Kleiber_2016,
   title={Visualizing Count Data Regressions Using Rootograms},
   volume={70},
   ISSN={1537-2731},
   url={http://dx.doi.org/10.1080/00031305.2016.1173590},
   DOI={10.1080/00031305.2016.1173590},
   number={3},
   journal={The American Statistician},
   publisher={Informa UK Limited},
   author={Kleiber, Christian and Zeileis, Achim},
   year={2016},
   month=jul, pages={296–303} }

@article{Brockmann_1996,
author = {Brockmann, H. Jane},
title = {Satellite Male Groups in Horseshoe Crabs, Limulus polyphemus},
journal = {Ethology},
volume = {102},
number = {1},
pages = {1-21},
doi = {10.1111/j.1439-0310.1996.tb01099.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1439-0310.1996.tb01099.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1439-0310.1996.tb01099.x},
year = {1996}
}

@book{tukey_1977,
	edition = {1 edition},
	title = {Exploratory {Data} {Analysis}},
	isbn = {978-0-201-07616-5},
	publisher = {Pearson},
	author = {Tukey, John W.},
	year = {1977},
    url = {https://archive.org/details/exploratorydataa0000tuke_7616/mode/2up},
}

@article{Greenhill_2011,
author = {Greenhill, Brian and Ward, Michael D. and Sacks, Audrey},
title = {The Separation Plot: A New Visual Method for Evaluating the Fit of Binary Models},
journal = {American Journal of Political Science},
volume = {55},
number = {4},
pages = {991-1002},
doi = {10.1111/j.1540-5907.2011.00525.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1540-5907.2011.00525.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1540-5907.2011.00525.x},
year = {2011}
}

@book{gelman_hill_2007,
  title = {Data Analysis Using Regression and Multilevel/Hierarchical Models},
  author = {Gelman, Andrew and Hill, Jennifer},
  publisher = {Cambridge University Press},
  address = {Cambridge},
  year = {2007},
  isbn = {9780521867061},
  url = {https://sites.stat.columbia.edu/gelman/arm/}
}

@article{kallioinen_2023,
	title = {Detecting and diagnosing prior and likelihood sensitivity with power-scaling},
	volume = {34},
	issn = {1573-1375},
	url = {https://doi.org/10.1007/s11222-023-10366-5},
	doi = {10.1007/s11222-023-10366-5},
	language = {en},
	number = {1},
	urldate = {2024-09-25},
	journal = {Statistics and Computing},
	author = {Kallioinen, Noa and Paananen, Topi and Bürkner, Paul-Christian and Vehtari, Aki},
	month = dec,
	year = {2023},
	keywords = {Artificial Intelligence, Bayesian, diagnostic, likelihood, prior, sensitivity},
	pages = {57},
}

@article{sailynoja_2022,
	title = {Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparison},
	volume = {32},
	issn = {1573-1375},
	url = {https://doi.org/10.1007/s11222-022-10090-6},
	doi = {10.1007/s11222-022-10090-6},
	language = {en},
	number = {2},
	urldate = {2024-10-07},
	journal = {Statistics and Computing},
	author = {Säilynoja, Teemu and Bürkner, Paul-Christian and Vehtari, Aki},
	month = mar,
	year = {2022},
	keywords = {Artificial Intelligence, ECDF, MCMC convergence diagnostic, PIT, Simulation-based calibration, Uniformity test},
	pages = {32},
}

@misc{talts_2020,
      title={Validating Bayesian Inference Algorithms with Simulation-Based Calibration}, 
      author={Sean Talts and Michael Betancourt and Daniel Simpson and Aki Vehtari and Andrew Gelman},
      year={2020},
      eprint={1804.06788},
      archivePrefix={arXiv},
      primaryClass={stat.ME},
      url={https://arxiv.org/abs/1804.06788}, 
}

@article{link_2011,
author = {Link, William A. and Eaton, Mitchell J.},
title = {On thinning of chains in MCMC},
journal = {Methods in Ecology and Evolution},
volume = {3},
number = {1},
pages = {112-115},
keywords = {Markov chain Monte Carlo, thinning, WinBUGS},
doi = {10.1111/j.2041-210X.2011.00131.x},
url = {https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/j.2041-210X.2011.00131.x},
eprint = {https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/j.2041-210X.2011.00131.x},
year = {2012},
}

@article{maceachern_1994,
	title = {Subsampling the {Gibbs} {Sampler}},
	volume = {48},
	issn = {0003-1305},
	url = {https://www.jstor.org/stable/2684714},
	doi = {10.2307/2684714},
	number = {3},
	urldate = {2024-10-07},
	journal = {The American Statistician},
	author = {MacEachern, Steven N. and Berliner, L. Mark},
	year = {1994},
	note = {Publisher: [American Statistical Association, Taylor \& Francis, Ltd.]},
	pages = {188--190},
}

@article{gelman_2017,
	title = {The {Prior} {Can} {Often} {Only} {Be} {Understood} in the {Context} of the {Likelihood}},
	volume = {19},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {1099-4300},
	url = {https://www.mdpi.com/1099-4300/19/10/555},
	doi = {10.3390/e19100555},
	language = {en},
	number = {10},
	urldate = {2024-12-06},
	journal = {Entropy},
	author = {Gelman, Andrew and Simpson, Daniel and Betancourt, Michael},
	month = oct,
	year = {2017},
	note = {Number: 10
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {Bayesian inference, default priors, prior distribution},
	pages = {555},
}

@article{mikkola_2024,
author = {Petrus Mikkola and Osvaldo A. Martin and Suyog Chandramouli and Marcelo Hartmann and Oriol Abril Pla and Owen Thomas and Henri Pesonen and Jukka Corander and Aki Vehtari and Samuel Kaski and Paul-Christian B{\"u}rkner and Arto Klami},
title = {{Prior Knowledge Elicitation: The Past, Present, and Future}},
volume = {19},
journal = {Bayesian Analysis},
number = {4},
publisher = {International Society for Bayesian Analysis},
pages = {1129 -- 1161},
keywords = {Bayesian workflow, domain knowledge, informative prior, prior distribution, prior elicitation},
year = {2024},
doi = {10.1214/23-BA1381},
URL = {https://doi.org/10.1214/23-BA1381}
}

@book{jaynes_2003,
	address = {Cambridge, UK ; New York, NY},
	title = {Probability {Theory}: {The} {Logic} of {Science}},
	isbn = {978-0-521-59271-0},
	shorttitle = {Probability {Theory}},
	abstract = {Going beyond the conventional mathematics of probability theory, this study views the subject in a wider context. It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.},
	publisher = {Cambridge University Press},
	author = {Jaynes, E. T.},
	editor = {Bretthorst, G. Larry},
	month = jun,
	year = {2003},
	url = {https://bayes.wustl.edu/etj/prob/book.pdf}
}

@article{icazatti_2023,
author = {Icazatti, Alejandro and Abril-Pla, Oriol and Klami, Arto and Martin, Osvaldo A},
doi = {10.21105/joss.05499},
journal = {Journal of Open Source Software},
month = sep,
number = {89},
pages = {5499},
title = {{PreliZ: A tool-box for prior elicitation}},
url = {https://joss.theoj.org/papers/10.21105/joss.05499},
volume = {8},
year = {2023}
}

@misc{gelman_2020,
      title={Bayesian Workflow}, 
      author={Andrew Gelman and Aki Vehtari and Daniel Simpson and Charles C. Margossian and Bob Carpenter and Yuling Yao and Lauren Kennedy and Jonah Gabry and Paul-Christian Bürkner and Martin Modrák},
      year={2020},
      eprint={2011.01808},
      archivePrefix={arXiv},
      primaryClass={stat.ME},
      url={https://arxiv.org/abs/2011.01808}, 
}

@article{morris_2014,
title = {A web-based tool for eliciting probability distributions from experts},
journal = {Environmental Modelling & Software},
volume = {52},
pages = {1-4},
year = {2014},
issn = {1364-8152},
doi = {10.1016/j.envsoft.2013.10.010},
url = {https://www.sciencedirect.com/science/article/pii/S1364815213002533},
author = {David E. Morris and Jeremy E. Oakley and John A. Crowe},
keywords = {Bayesian prior distribution, Expert judgement, Subjective probability, Web-based elicitation}
}

@book{martin_2021,
	address = {Boca Raton London New York},
	edition = {1st edition},
	title = {Bayesian {Modeling} and {Computation} in {Python}},
	isbn = {978-0-367-89436-8},
	language = {English},
	publisher = {Chapman and Hall/CRC},
	author = {Martin, Osvaldo A. and Kumar, Ravin and Lao, Junpeng},
	month = dec,
	year = {2021},
	url = {https://bayesiancomputationbook.com/}
}

@book{martin_2024,
	title = {Bayesian {Analysis} with {Python}: {A} {Practical} {Guide} to probabilistic modeling, 3rd {Edition}},
	isbn = {978-1-80512-716-1},
	shorttitle = {Bayesian {Analysis} with {Python}},
	language = {English},
	publisher = {Packt Publishing},
	author = {Martin, Osvaldo A},
	month = feb,
	year = {2024},
	url = {https://bap.com.ar/}
}
           
@article{chipman_2010,
	title = {{BART}: {Bayesian} additive regression trees},
	volume = {4},
	issn = {1932-6157},
	shorttitle = {{BART}},
	url = {http://projecteuclid.org/euclid.aoas/1273584455},
	doi = {10.1214/09-AOAS285},
	language = {en},
	number = {1},
	urldate = {2019-02-21},
	journal = {The Annals of Applied Statistics},
	author = {Chipman, Hugh A. and George, Edward I. and McCulloch, Robert E.},
	month = mar,
	year = {2010},
	pages = {266--298},
}

@article{vehtari_2017,
  author = {Vehtari, Aki and Gelman, Andrew and Gabry, Jonah},
  title = {Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC},
  journal = {Statistics and Computing},
  year = {2017},
  volume = {27},
  number = {5},
  pages = {1413--1432},
  doi = {10.1007/s11222-016-9696-4},
  url = {https://doi.org/10.1007/s11222-016-9696-4},
}

@article{yao_2018,
author = {Yuling Yao and Aki Vehtari and Daniel Simpson and Andrew Gelman},
title = {{Using Stacking to Average Bayesian Predictive Distributions (with Discussion)}},
volume = {13},
journal = {Bayesian Analysis},
number = {3},
publisher = {International Society for Bayesian Analysis},
pages = {917 -- 1007},
keywords = {Bayesian model averaging, model combination, predictive distribution, proper scoring rule, stacking, Stan},
year = {2018},
doi = {10.1214/17-BA1091},
URL = {https://doi.org/10.1214/17-BA1091},
}

@article{watanabe_2013,
	title = {A {Widely} {Applicable} {Bayesian} {Information} {Criterion}},
	volume = {14},
	journal = {Journal of Machine Learning Research},
	author = {Watanabe, Sumio},
	month = mar,
	year = {2013},
	pages = {867--897},
	url = {https://dl.acm.org/doi/10.5555/2567709.2502609}
}

@article{akaike_1974,
  author={Akaike, H.},
  journal={IEEE Transactions on Automatic Control}, 
  title={A new look at the statistical model identification}, 
  year={1974},
  volume={19},
  number={6},
  pages={716-723},
  doi={10.1109/TAC.1974.1100705},
  }

@article{vehtari_2021,
author = {Aki Vehtari and Andrew Gelman and Daniel Simpson and Bob Carpenter and Paul-Christian B{\"u}rkner},
title = {{Rank-Normalization, Folding, and Localization: An Improved $\widehat{R}$ for Assessing Convergence of MCMC (with Discussion)}},
volume = {16},
journal = {Bayesian Analysis},
number = {2},
publisher = {International Society for Bayesian Analysis},
pages = {667 -- 718},
year = {2021},
doi = {10.1214/20-BA1221},
URL = {https://doi.org/10.1214/20-BA1221}
}


@article{ionides_2008,
  author = {Edward L. Ionides},
  title = {Truncated Importance Sampling},
  journal = {Journal of Computational and Graphical Statistics},
  year = {2008},
  volume = {17},
  number = {2},
  pages = {295--311},
  doi = {10.1198/106186008X320465}
}

@article{bengio_2004,
  author = {Bengio, Yoshua and Grandvalet, Yves},
  title = {No Unbiased Estimator of the Variance of K-Fold Cross-Validation},
  journal = {Journal of Machine Learning Research},
  year = {2004},
  volume = {5},
  pages = {1089--1105},
  url = {https://jmlr.csail.mit.edu/papers/v5/grandvalet04a.html}
}

@article{hansen_hurwitz_1943,
  author = {Hansen, Morris H. and Hurwitz, William N.},
  title = {On the Theory of Sampling from Finite Populations},
  journal = {The Annals of Mathematical Statistics},
  year = {1943},
  volume = {14},
  number = {4},
  pages = {333--362},
  doi = {10.1214/aoms/1177731360}
}

@inproceedings{magnusson_2019,
  title = {Bayesian leave-one-out cross-validation for large data},
  author = {M\aa ns Magnusson and Michael Andersen and Johan Jonasson and Aki Vehtari},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning},
  series = {Proceedings of Machine Learning Research},
  volume = {97},
  pages = {4244--4253},
  year = {2019},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v97/magnusson19a.html}
}

@inproceedings{magnusson_2020,
  title = {Leave-One-Out Cross-Validation for Model Comparison in Large Data},
  author = {M\aa ns Magnusson and Michael Riis Andersen and Johan Jonasson and Aki Vehtari},
  booktitle = {Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics},
  series = {Proceedings of Machine Learning Research},
  volume = {108},
  year = {2020},
  publisher = {PMLR},
  url = {https://arxiv.org/abs/2001.00980}
}


@article{piironen_2020,
author = {Juho Piironen and Markus Paasiniemi and Aki Vehtari},
title = {{Projective inference in high-dimensional problems: Prediction and feature selection}},
volume = {14},
journal = {Electronic Journal of Statistics},
number = {1},
publisher = {Institute of Mathematical Statistics and Bernoulli Society},
pages = {2155 -- 2197},
keywords = {Feature selection, Post-selection inference, prediction, projection, Sparsity},
year = {2020},
doi = {10.1214/20-EJS1711},
URL = {https://doi.org/10.1214/20-EJS1711}
}

@misc{quiroga_2022,
  doi = {10.48550/ARXIV.2206.03619},
  url = {https://arxiv.org/abs/2206.03619},
  author = {Quiroga, Miriana and Garay, Pablo G and Alonso, Juan M. and Loyola, Juan Martin and Martin, Osvaldo A},
  keywords = {Computation (stat.CO), FOS: Computer and information sciences, FOS: Computer and information sciences},
  title = {Bayesian additive regression trees for probabilistic programming},
  publisher = {arXiv},
  year = {2022},
  copyright = {Creative Commons Attribution Share Alike 4.0 International}
}

@misc{mclatchie_2023,
    title={Robust and efficient projection predictive inference},
    author={Yann McLatchie and Sölvi Rögnvaldsson and Frank Weber and Aki Vehtari},
    year={2023},
    eprint={2306.15581},
    archivePrefix={arXiv},
    primaryClass={stat.ME}
}

@misc{paananen_2020,
  title = {Implicitly Adaptive Importance Sampling},
  author = {Paananen, Topi and Piironen, Juho and B{\"u}rkner, Paul-Christian and Vehtari, Aki},
  year = {2020},
  eprint = {1906.08850},
  archivePrefix = {arXiv},
  primaryClass = {stat.CO},
  url = {https://arxiv.org/abs/1906.08850}
}

@article{johnson_1996,
author = {Roger W. Johnson},
title = {Fitting Percentage of Body Fat to Simple Body Measurements},
journal = {Journal of Statistics Education},
volume = {4},
number = {1},
pages = {},
year = {1996},
publisher = {Taylor \& Francis},
doi = {10.1080/10691898.1996.11910505},
URL = {https://doi.org/10.1080/10691898.1996.11910505},
eprint = {https://doi.org/10.1080/10691898.1996.11910505}}

@InProceedings{nguyen_2015,
author="Nguyen, Hoang-Vu
and Vreeken, Jilles",
editor="Appice, Annalisa
and Rodrigues, Pedro Pereira
and Santos Costa, V{\'i}tor
and Gama, Jo{\~a}o
and Jorge, Al{\'i}pio
and Soares, Carlos",
title="Non-parametric Jensen-Shannon Divergence",
booktitle="Machine Learning and Knowledge Discovery in Databases",
year="2015",
publisher="Springer International Publishing",
address="Cham",
pages="173--189",
doi="10.1007/978-3-319-23525-7_11",
url="https://doi.org/10.1007/978-3-319-23525-7_11"
}

@book{venables_2002,
	address = {New York},
	edition = {4th edition},
	title = {Modern {Applied} {Statistics} with {S}},
	isbn = {978-0-387-95457-8},
	language = {English},
	publisher = {Springer},
	author = {Venables, W. N. and Ripley, B. D.},
	month = aug,
	year = {2002},
	doi = {10.1007/978-0-387-21706-2},
	url = {https://doi.org/10.1007/978-0-387-21706-2}
}

@article{Brockmann_1996,
author = {Brockmann, H. Jane},
title = {Satellite Male Groups in Horseshoe Crabs, Limulus polyphemus},
journal = {Ethology},
volume = {102},
number = {1},
pages = {1-21},
doi = {10.1111/j.1439-0310.1996.tb01099.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1439-0310.1996.tb01099.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1439-0310.1996.tb01099.x},
year = {1996}
}

@misc{Säilynoja_2025,
    title={Recommendations for visual predictive checks in Bayesian workflow},
    author={Teemu Säilynoja and Andrew R. Johnson and Osvaldo A. Martin and Aki Vehtari},
    year={2025},
    eprint={2503.01509},
    archivePrefix={arXiv},
    primaryClass={stat.ME}
}

@article{Gabry_2019,
    author = {Gabry, Jonah and Simpson, Daniel and Vehtari, Aki and Betancourt, Michael and Gelman, Andrew},
    title = {Visualization in Bayesian Workflow},
    journal = {Journal of the Royal Statistical Society Series A: Statistics in Society},
    volume = {182},
    number = {2},
    pages = {389-402},
    year = {2019},
    month = {01},
    issn = {0964-1998},
    doi = {10.1111/rssa.12378},
    url = {https://doi.org/10.1111/rssa.12378},
    eprint = {https://academic.oup.com/jrsssa/article-pdf/182/2/389/49429057/jrsssa\_182\_2\_389.pdf},
}


@article{Meng_1994,
author = {Xiao-Li Meng},
title = {{Posterior Predictive $p$-Values}},
volume = {22},
journal = {The Annals of Statistics},
number = {3},
publisher = {Institute of Mathematical Statistics},
pages = {1142 -- 1160},
keywords = {$p$-value, Bayesian $p$-value, Behrens-Fisher problem, Discrepancy, multiple imputation, nuisance parameter, pivot, significance level, tail-area probability, test variable, Type I error},
year = {1994},
doi = {10.1214/aos/1176325622},
URL = {https://doi.org/10.1214/aos/1176325622}
}

@book{Gelman_2013,
	address = {Boca Raton},
	title = {Bayesian {Data} {Analysis}},
	isbn = {978-1-4398-4095-5},
	url = {https://doi.org/10.1201/b16018},
	language = {Inglés},
	author = {Gelman, Andrew and Carlin, John B. and Stern, Hal S. and Dunson, David B. and Vehtari, Aki and Rubin, Donald B.},
	month = nov,
	year = {2013},
}

@article{Gelman_2013b,
author = {Andrew Gelman},
title = {{Two simple examples for understanding posterior p-values whose distributions are far from uniform}},
volume = {7},
journal = {Electronic Journal of Statistics},
number = {none},
publisher = {Institute of Mathematical Statistics and Bernoulli Society},
pages = {2595 -- 2602},
keywords = {Bayesian inference, model checking, posterior predictive check, p-value, u-value},
year = {2013},
doi = {10.1214/13-EJS854},
URL = {https://doi.org/10.1214/13-EJS854}
}

@article{Dimitriadis_2021,
	title = {Stable reliability diagrams for probabilistic classifiers},
	volume = {118},
	url = {https://www.pnas.org/doi/abs/10.1073/pnas.2016191118},
	doi = {10.1073/pnas.2016191118},
	number = {8},
	urldate = {2025-03-07},
	journal = {Proceedings of the National Academy of Sciences},
	author = {Dimitriadis, Timo and Gneiting, Tilmann and Jordan, Alexander I.},
	month = feb,
	year = {2021},
	note = {Publisher: Proceedings of the National Academy of Sciences},
	pages = {e2016191118},
}

@article{Ayer_1955,
author = {Miriam Ayer and H. D. Brunk and G. M. Ewing and W. T. Reid and Edward Silverman},
title = {{An Empirical Distribution Function for Sampling with Incomplete Information}},
volume = {26},
journal = {The Annals of Mathematical Statistics},
number = {4},
publisher = {Institute of Mathematical Statistics},
pages = {641 -- 647},
year = {1955},
doi = {10.1214/aoms/1177728423},
URL = {https://doi.org/10.1214/aoms/1177728423}
}

@article{mikkola_2024,
  author    = {Petrus Mikkola and Osvaldo A. Martin and Suyog Chandramouli and Marcelo Hartmann and Oriol Abril Pla and Owen Thomas and Henri Pesonen and Jukka Corander and Aki Vehtari and Samuel Kaski and Paul-Christian B{\"u}rkner and Arto Klami},
  title     = {Prior Knowledge Elicitation: The Past, Present, and Future},
  journal   = {Bayesian Analysis},
  volume    = {19},
  number    = {4},
  pages     = {1129--1161},
  year      = {2024},
  month     = dec,
  doi       = {10.1214/23-BA1381}
}

@article{Cook_2006,
author = {Samantha R Cook and Andrew Gelman and Donald B Rubin and},
title = {Validation of Software for Bayesian Models Using Posterior Quantiles},
journal = {Journal of Computational and Graphical Statistics},
volume = {15},
number = {3},
pages = {675--692},
year = {2006},
publisher = {ASA Website},
doi = {10.1198/106186006X136976},
URL = {https://doi.org/10.1198/106186006X136976},
eprint = {https://doi.org/10.1198/106186006X136976}}

@article{Modrak_2025,
author = {Martin Modr{\'a}k and Angie H. Moon and Shinyoung Kim and Paul B{\"u}rkner and Niko Huurre and Kateřina Faltejskov{\'a} and Andrew Gelman and Aki Vehtari},
title = {{Simulation-Based Calibration Checking for Bayesian Computation: The Choice of Test Quantities Shapes Sensitivity}},
volume = {20},
journal = {Bayesian Analysis},
number = {2},
publisher = {International Society for Bayesian Analysis},
pages = {461 -- 488},
keywords = {Calibration, probabilistic programming, Software testing},
year = {2025},
doi = {10.1214/23-BA1404},
URL = {https://doi.org/10.1214/23-BA1404}
}

@misc{Betancourt_2016,
      title={Diagnosing Suboptimal Cotangent Disintegrations in Hamiltonian Monte Carlo},
      author={Michael Betancourt},
      year={2016},
      eprint={1604.00695},
      archivePrefix={arXiv},
      primaryClass={stat.ME},
      url={https://arxiv.org/abs/1604.00695},
}

@misc{Säilynoja_2025b,
      title={Posterior SBC: Simulation-Based Calibration Checking Conditional on Data}, 
      author={Teemu Säilynoja and Marvin Schmitt and Paul-Christian Bürkner and Aki Vehtari},
      year={2025},
      eprint={2502.03279},
      archivePrefix={arXiv},
      primaryClass={stat.ME},
      url={https://arxiv.org/abs/2502.03279}, 
}

@article{kruschke_2021,
	title = {Bayesian {Analysis} {Reporting} {Guidelines}},
	volume = {5},
	copyright = {2021 The Author(s)},
	issn = {2397-3374},
	url = {https://www.nature.com/articles/s41562-021-01177-7},
	doi = {10.1038/s41562-021-01177-7},
	language = {en},
	number = {10},
	urldate = {2025-07-28},
	journal = {Nature Human Behaviour},
	author = {Kruschke, John K.},
	month = oct,
	year = {2021},
	note = {Publisher: Nature Publishing Group},
	keywords = {Medical research, Psychology},
	pages = {1282--1291},
}

@article{martin_2022,
	title = {A call for changing data analysis practices: from philosophy and comprehensive reporting to modeling approaches and back},
	volume = {476},
	issn = {1573-5036},
	shorttitle = {A call for changing data analysis practices},
	url = {https://doi.org/10.1007/s11104-022-05329-0},
	doi = {10.1007/s11104-022-05329-0},
	language = {en},
	number = {1},
	urldate = {2025-07-28},
	journal = {Plant and Soil},
	author = {Martin, Osvaldo A. and Teste, François P.},
	month = jul,
	year = {2022},
	keywords = {Applied Statistics, Bayesian and frequentist inference, Biostatistics, Confidence intervals, Effect sizes, p-values, Statistical models, Statistical Software, Statistics, Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics in Social Sciences},
	pages = {743--753},
  }


@book{brooks_2011,
	address = {Boca Raton},
	edition = {1 edition},
	title = {Handbook of {Markov} {Chain} {Monte} {Carlo}},
	isbn = {978-1-4200-7941-8},
	url = {https://doi.org/10.1201/b10905},
	publisher = {Chapman and Hall/CRC},
	editor = {Brooks, Steve and Gelman, Andrew and Jones, Galin and Meng, Xiao-Li},
	month = may,
	year = {2011},
}

@book{tadesse_2022,
	address = {Boca Raton},
	title = {Handbook of {Bayesian} {Variable} {Selection}},
	isbn = {978-0-367-54376-1},
	url = {https://doi.org/10.1201/9781003089018},
	language = {English},
	publisher = {Chapman and Hall/CRC},
	editor = {Tadesse, Mahlet G. and Vannucci, Marina},
	year = {2022},
}

@book{downey_2025,
	address = {Sebastopol},
	title = {Think {Stats}: {Exploratory} {Data} {Analysis}},
	isbn = {978-1-09-819025-5},
	url = {https://allendowney.github.io/ThinkStats/},
	shorttitle = {Think {Stats}},
	language = {English},
	publisher = {O'Reilly Media},
	author = {Downey, Allen B.},
	year = {2025},
}


@book{wilke_2019,
	address = {Beijing Boston Farnham Sebastopol Tokyo},
	title = {Fundamentals of {Data} {Visualization}: {A} {Primer} on {Making} {Informative} and {Compelling} {Figures}},
	isbn = {978-1-4920-3108-6},
	url = {https://clauswilke.com/dataviz/},
	shorttitle = {Fundamentals of {Data} {Visualization}},
	language = {English},
	publisher = {O'Reilly Media},
	author = {Wilke, Claus O.},
	year = {2019},
}

@book{healy_2019,
	address = {Princeton, New Jersey ; Oxford, Oxfordshire},
	title = {Data {Visualization}: {A} {Practical} {Introduction}},
	isbn = {978-0-691-18162-2},
	url = {https://kieranhealy.org/publications/dataviz/},
	shorttitle = {Data {Visualization}},
	language = {English},
	publisher = {Princeton University Press},
	author = {Healy, Kieran},
	year = {2019},
}

@book{unwin_2024,
	address = {Boca Raton},
	title = {Getting (more out of) {Graphics}: {Practice} and {Principles} of {Data} {Visualisation}},
	isbn = {978-1-04-003556-6},
	url = {https://doi.org/10.1201/9781003131212},
	language = {English},
	publisher = {Chapman and Hall/CRC},
	author = {Unwin, Antony},
	year = {2024},
}

@inproceedings{kay_2016,
	address = {New York, NY, USA},
	series = {{CHI} '16},
	title = {When (ish) is {My} {Bus}? {User}-centered {Visualizations} of {Uncertainty} in {Everyday}, {Mobile} {Predictive} {Systems}},
	isbn = {978-1-4503-3362-7},
	shorttitle = {When (ish) is {My} {Bus}?},
	url = {https://doi.org/10.1145/2858036.2858558},
	doi = {10.1145/2858036.2858558},
	booktitle = {Proceedings of the 2016 {CHI} {Conference} on {Human} {Factors} in {Computing} {Systems}},
	publisher = {Association for Computing Machinery},
	author = {Kay, Matthew and Kola, Tara and Hullman, Jessica R. and Munson, Sean A.},
	month = may,
	year = {2016},
	pages = {5092--5103},
}

@article{wilkinson_1999,
	title = {Dot {Plots}},
	volume = {53},
	issn = {0003-1305},
	url = {https://www.tandfonline.com/doi/abs/10.1080/00031305.1999.10474474},
	doi = {10.1080/00031305.1999.10474474},
	number = {3},
	urldate = {2025-08-11},
	journal = {The American Statistician},
	author = {Wilkinson, Leland},
	month = aug,
	year = {1999},
	note = {Publisher: ASA Website},
	keywords = {Dotplot, Graphics, Histogram, Kernel density estimation},
	pages = {276--281},
}

@inproceedings{fernandes_2018,
	address = {New York, NY, USA},
	series = {{CHI} '18},
	title = {Uncertainty {Displays} {Using} {Quantile} {Dotplots} or {CDFs} {Improve} {Transit} {Decision}-{Making}},
	isbn = {978-1-4503-5620-6},
	url = {https://doi.org/10.1145/3173574.3173718},
	doi = {10.1145/3173574.3173718},
	urldate = {2025-08-10},
	booktitle = {Proceedings of the 2018 {CHI} {Conference} on {Human} {Factors} in {Computing} {Systems}},
	publisher = {Association for Computing Machinery},
	author = {Fernandes, Michael and Walls, Logan and Munson, Sean and Hullman, Jessica and Kay, Matthew},
	month = apr,
	year = {2018},
	pages = {1--12},
}

@misc{soch_2024,
	title={The Book of Statistical Proofs},
	author={Soch, Joram and Faulkenberry, Thomas J and Petrykowski, Kenneth and Allefeld, Carsten},
	year={2024},
	doi={10.5281/ZENODO.4305949},
	url={https://statproofbook.github.io/}
}

@misc{suorsa_2026,
      title={Predictive Assessment and Comparison of Bayesian Survival Models for Cancer Recurrence}, 
      author={Saku Suorsa and Aki Vehtari},
      year={2026},
      eprint={2601.01662},
      archivePrefix={arXiv},
      primaryClass={stat.ME},
      url={https://arxiv.org/abs/2601.01662}, 
}


@book{mcelreath_2020,
	address = {Boca Raton},
	title = {Statistical {Rethinking}: {A} {Bayesian} {Course} with {Examples} in {R} and {STAN}},
	isbn = {978-0-367-13991-9},
	shorttitle = {Statistical {Rethinking}},
	language = {English},
	publisher = {Chapman and Hall/CRC},
	author = {McElreath, Richard},
	year = {2020},
    url = {https://doi.org/10.1201/9780429029608},
}

@misc{tesso_2026,
      title={LOO-PIT predictive model checking},
      author={Herman Tesso and Aki Vehtari},
      year={2026},
      eprint={2603.02928},
      archivePrefix={arXiv},
      primaryClass={stat.ME},
      url={https://arxiv.org/abs/2603.02928},
}