BookCode_Edition1/bibtex.bib at quartet · BayesianModelingandComputationInPython/BookCode_Edition1

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@book{GelmanBayesianDataAnalysis2013,
    title={Bayesian Data Analysis, Third Edition},
    author={Gelman, A. and Carlin, J.B. and Stern, H.S. and Dunson, D.B. and Vehtari, A. and Rubin, D.B.},
    isbn={9781439840955},
    lccn={2013039507},
    series={Chapman \& Hall/CRC Texts in Statistical Science},
    year={2013},
    publisher={Taylor \& Francis}
@book{WoodGeneralizedAdditiveModels2017,
    title={Generalized Additive Models: An Introduction with R, Second Edition},
    author={Wood, S.N.},
    isbn={9781498728379},
    series={Chapman \& Hall/CRC Texts in Statistical Science},
    year={2017},
    publisher={CRC Press}
@article{ChipmanBARTBayesianadditive2010,
    title={BART: Bayesian additive regression trees},
    author={Chipman, Hugh A. and George, Edward I. and McCulloch, Robert E.},
    journal={The Annals of Applied Statistics},
    volume={4},
    number={1},
    pages={266--298},
    year={2010},
    publisher={Institute of Mathematical Statistics}
@book{ZhouEnsembleMethods2012,
    title={Ensemble Methods: Foundations and Algorithms},
    author={Zhou, Z.H.},
    isbn={9781439830055},
    lccn={2012014555},
    series={Chapman \& Hall/CRC data mining and knowledge discovery series},
    year={2012},
    publisher={CRC Press}
@inproceedings{royMondrianProcess,
    title={The Mondrian process},
    author={Roy, Daniel M and Teh, Yee Whye},
    booktitle={Proceedings of the 21st International Conference on Neural Information Processing Systems},
    pages={1377--1384},
    year={2008}
@article{BalogMondrianProcessMachine2015,
    title={The Mondrian process for machine learning},
    author={Balog, Matej and Teh, Yee Whye},
    journal={arXiv preprint arXiv:1507.05181},
    year={2015}
@inproceedings{Lakshminarayanan,
    title={Particle Gibbs for Bayesian additive regression trees},
    author={Lakshminarayanan, Balaji and Roy, Daniel and Teh, Yee Whye},
    booktitle={Artificial Intelligence and Statistics},
    pages={553--561},
    year={2015},
    organization={PMLR}
@book{blitzstein_2019,
    title={Introduction to Probability, Second Edition},
    author={Blitzstein, J.K. and Hwang, J.},
    isbn={9780429766732},
    lccn={2020693004},
    series={Chapman \& Hall/CRC Texts in Statistical Science},
    year={2019},
    publisher={CRC Press}
@article{Kumar2019,
    title={ArviZ a unified library for exploratory analysis of Bayesian models in Python},
    author={Kumar, Ravin and Carroll, Colin and Hartikainen, Ari and Martin, Osvaldo},
    journal={Journal of Open Source Software},
    volume={4},
    number={33},
    pages={1143},
    year={2019},
    publisher={The Open Journal}
@book{cox_2006,
    place={Cambridge},
    title={Principles of statistical inference},
    publisher={Cambridge University Press},
	isbn = {978-0521685672},
	language = {English},
    author={Cox, D. R.},
    year={2006},
    pages = {178}
@article{vehtari_rank_2019,
    author = {Aki Vehtari and Andrew Gelman and Daniel Simpson and Bob Carpenter and Paul-Christian Bürkner},
    title = {{Rank-Normalization, Folding, and Localization: An Improved $\widehat{R}$ for Assessing Convergence of MCMC}},
    journal = {Bayesian Analysis},
    publisher = {International Society for Bayesian Analysis},
    pages = {1 -- 38},
    year = {2021},
    doi = {10.1214/20-BA1221},
    URL = {https://doi.org/10.1214/20-BA1221}
@article{watanabe2010asymptotic,
    title={Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory.},
    author={Watanabe, Sumio and Opper, Manfred},
    journal={Journal of machine learning research},
    volume={11},
    number={12},
    year={2010}
@article{kruschke_2013,
    title={Bayesian estimation supersedes the t test.},
    author={Kruschke, John K},
    journal={Journal of Experimental Psychology: General},
    volume={142},
    number={2},
    pages={573},
    year={2013},
    publisher={American Psychological Association}
@article{10.2307/2979084,
    title={The mathematical theory of banking},
    author={Edgeworth, Francis Y},
    journal={Journal of the Royal Statistical Society},
    volume={51},
    number={1},
    pages={113--127},
    year={1888},
    publisher={JSTOR}
@book{Cover_Thomas,
    title={Elements of Information Theory},
    author={Cover, T.M. and Thomas, J.A.},
    isbn={9781118585771},
    lccn={2005047799},
    year={2012},
    publisher={Wiley}
@article{gneiting_2007,
    title={Strictly proper scoring rules, prediction, and estimation},
    author={Gneiting, Tilmann and Raftery, Adrian E},
    journal={Journal of the American statistical Association},
    volume={102},
    number={477},
    pages={359--378},
    year={2007},
    publisher={Taylor \& Francis}
@article{vehtari_pareto_2019,
    title={Pareto smoothed importance sampling},
    author={Vehtari, Aki and Simpson, Daniel and Gelman, Andrew and Yao, Yuling and Gabry, Jonah},
    journal={arXiv preprint arXiv:1507.02646},
    year={2021}
@article{gabry_visualization_2017,
    title={Visualization in Bayesian workflow},
    author={Gabry, Jonah and Simpson, Daniel and Vehtari, Aki and Betancourt, Michael and Gelman, Andrew},
    journal={Journal of the Royal Statistical Society: Series A (Statistics in Society)},
    volume={182},
    number={2},
    pages={389--402},
    year={2019},
    publisher={Wiley Online Library}

17A6
@article{vehtari_practical_2017,
    title={Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC},
    author={Vehtari, Aki and Gelman, Andrew and Gabry, Jonah},
    journal={Statistics and computing},
    volume={27},
    number={5},
    pages={1413--1432},
    year={2017},
    publisher={Springer}
@article{yao_stacking_2018,
    title={Using stacking to average Bayesian predictive distributions (with discussion)},
    author={Yao, Yuling and Vehtari, Aki and Simpson, Daniel and Gelman, Andrew},
    journal={Bayesian Analysis},
    volume={13},
    number={3},
    pages={917--1007},
    year={2018},
    publisher={International Society for Bayesian Analysis}
@incollection{akaike_1973,
    title={Information theory and an extension of the maximum likelihood principle},
    author={Akaike, Hirotogu},
    booktitle={Selected papers of hirotugu akaike},
    pages={199--213},
    year={1998},
    publisher={Springer}
@book{gilks1995markov,
    title={Markov Chain Monte Carlo in Practice},
    author={Gilks, W.R. and Richardson, S. and Spiegelhalter, D.},
    isbn={9781482214970},
    series={Chapman \& Hall/CRC Interdisciplinary Statistics},
    year={1995},
    publisher={CRC Press}
@misc{wikipedia_model_2020,
    author = {Wikipedia contributors},
    title = {Conceptual model --- {W}ikipedia{,} The Free Encyclopedia},
    url = {https://en.wikipedia.org/w/index.php?title=Conceptual_model&oldid=952394363},
    note = {Page Version ID: 952394363},
@article{hoeting_bayesian_1999,
    title={Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and EI George, and a rejoinder by the authors},
    author={Hoeting, Jennifer A and Madigan, David and Raftery, Adrian E and Volinsky, Chris T},
    journal={Statistical science},
    volume={14},
    number={4},
    pages={382--417},
    year={1999},
    publisher={Institute of Mathematical Statistics}
@inbook{Diaconis2011,
    author = {Diaconis, Persi},
    publisher = {John Wiley \& Sons, Ltd},
    isbn = {9781118150702},
    title = {Theories of Data Analysis: From Magical Thinking Through Classical Statistics},
    booktitle = {Exploring Data Tables, Trends, and Shapes},
    chapter = {1},
    pages = {1-36},
    year = {2006},
    keywords = {data analysis, intuitive statistics, multiplicity, controlled magical thinking, data structure},
    abstract = {Summary 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}
@book{WestfallUnderstandingAdvancedStatistical2013,
    title={Understanding Advanced Statistical Methods},
    author={Westfall, P. and Henning, K.S.S.},
    isbn={9781466512108},
    lccn={2013003655},
    series={Chapman \& Hall/CRC Texts in Statistical Science},
    year={2013},
    publisher={Taylor \& Francis}
@article{Neal_1994,
    title={Contribution to the discussion of “Approximate Bayesian inference with the weighted likelihood bootstrap” by Michael A. Newton and Adrian E. Raftery},
    author={Neal, Radford M},
    journal = {Journal of the Royal Statistical Society. Series B (Methodological)},
    volume={56},
    pages={41--42},
    year={1994}
@article{Friel_2011,
    title={Estimating the evidence--a review},
    author={Friel, Nial and Wyse, Jason},
    journal={Statistica Neerlandica},
    volume={66},
    number={3},
    pages={288--308},
    year={2012},
    publisher={Wiley Online Library}
@inproceedings{Robert_2009,
    title={Computational methods for Bayesian model choice},
    author={Robert, Christian P and Wraith, Darren},
    booktitle={Aip conference proceedings},
    volume={1193},
    number={1},
    pages={251--262},
    year={2009},
    organization={American Institute of Physics}
@article{clark_westerberg_2009,
    title={How random is the toss of a coin?},
    author={Clark, Matthew PA. and Westerberg, Brian D.},
    journal={Cmaj},
    volume={181},
    number={12},
    pages={E306--E308},
    year={2009},
    publisher={Can Med Assoc}
@book{mcelreath_2020,
    title={Statistical Rethinking: A Bayesian Course with Examples in R and Stan},
    author={McElreath, R.},
    isbn={9781482253481},
    series={Chapman \& Hall/CRC Texts in Statistical Science},
    year={2020},
    publisher={CRC Press}
@book{tukey77,
    title={Exploratory Data Analysis},
    publisher={Addison-Wesley},
    author={Tukey, John W.},
    year={1977},
@article{Naesseth2019,
    title={Elements of sequential monte carlo},
    author={Naesseth, Christian A and Lindsten, Fredrik and Sch{\"o}n, Thomas B},
    journal={arXiv preprint arXiv:1903.04797},
    year={2019}
@article{Ching2007,
    title={Transitional Markov chain Monte Carlo method for Bayesian model updating, model class selection, and model averaging},
    author={Ching, Jianye and Chen, Yi-Chu},
    journal={Journal of engineering mechanics},
    volume={133},
    number={7},
    pages={816--832},
    year={2007},
    publisher={American Society of Civil Engineers}
@article{delmoral2006,
    title={Sequential monte carlo samplers},
    author={Del Moral, Pierre and Doucet, Arnaud and Jasra, Ajay},
    journal={Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
    volume={68},
    number={3},
    pages={411--436},
    year={2006},
    publisher={Wiley Online Library}
@book{Chopin2020,
    title={An Introduction to Sequential Monte Carlo},
    author={Chopin, N. and Papaspiliopoulos, O.},
    isbn={9783030478445},
    series={Springer Series in Statistics},
    year={2020},
    publisher={Springer International Publishing}
@article{Marin2012,
    title={Approximate Bayesian computational methods},
    author={Marin, Jean-Michel and Pudlo, Pierre and Robert, Christian P and Ryder, Robin J},
    journal={Statistics and Computing},
    volume={22},
    number={6},
    pages={1167--1180},
    year={2012},
    publisher={Springer}
@inproceedings{Tukey1977,
  title = {Modern {{Techniques}} in {{Data Analysis}}},
  booktitle = {proceesings of the Sponsored Regional Research Conference},
  author = {Tukey, John W.},
  year = {1977},
  location = {{Southern Massachusetts University, North Dartmouth}},
  eventtitle = {{{SF}}-{{Sponsored Regional Research Conference}}}
@article{Rayner2002,
    title={Numerical maximum likelihood estimation for the g-and-k and generalized g-and-h distributions},
    author={Rayner, Glen D and MacGillivray, Helen L},
    journal={Statistics and Computing},
    volume={12},
    number={1},
    pages={57--75},
    year={2002},
    publisher={Springer}
@article{Drovandi2011,
    title={Likelihood-free Bayesian estimation of multivariate quantile distributions},
    author={Drovandi, Christopher C and Pettitt, Anthony N},
    journal={Computational Statistics \& Data Analysis},
    volume={55},
    number={9},
    pages={2541--2556},
    year={2011},
    publisher={Elsevier}
@book{Bowley1920,
    title={Elements of Statistics},
    author={Bowley, A.L.},
    number={v. 2},
    lccn={24012093},
    series={Elements of Statistics},
    year={1920},
    publisher={P.S. King}
@article{Moors1988,
    title={A quantile alternative for kurtosis},
    author={Moors, JJA},
    journal={Journal of the Royal Statistical Society: Series D (The Statistician)},
    volume={37},
    number={1},
    pages={25--32},
    year={1988},
    publisher={Wiley Online Library}
@article{prangle2017,
    title={gk: An R package for the g-and-k and generalised g-and-h distributions},
    author={Prangle, Dennis},
    journal={arXiv preprint arXiv:1706.06889},
    year={2017}
@article{Bernton_2019,
    title={Approximate Bayesian computation with the Wasserstein distance},
    author={Bernton, Espen and Jacob, Pierre E and Gerber, Mathieu and Robert, Christian P},
    journal={Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
    volume={81},
    number={2},
    pages={235--269},
    year={2019},
    publisher={Wiley Online Library}
@inproceedings{Jiang2018,
    title={Approximate Bayesian computation with Kullback-Leibler divergence as data discrepancy},
    author={Jiang, Bai},
    booktitle={International conference on artificial intelligence and statistics},
    pages={1711--1721},
    year={2018},
    organization={PMLR}
@inproceedings{Perez2008,
    title={Kullback-Leibler divergence estimation of continuous distributions},
    author={P{\'e}rez-Cruz, Fernando},
    booktitle={2008 IEEE international symposium on information theory},
    pages={1666--1670},
    year={2008},
    organization={IEEE}
@article{Bentley1975,
    title={Multidimensional binary search trees used for associative searching},
    author={Bentley, Jon Louis},
    journal={Communications of the ACM},
    volume={18},
    number={9},
    pages={509--517},
    year={1975},
    publisher={ACM New York, NY, USA}
@book{Sisson2018,
    title={Handbook of Approximate Bayesian Computation},
    author={Sisson, S.A. and Fan, Y. and Beaumont, M.},
    isbn={9781439881514},
    lccn={2019717481},
    series={Chapman \& Hall/CRC Handbooks of Modern Statistical Methods},
    year={2018},
    publisher={CRC Press}
@article{Pudlo2015,
    title={Reliable ABC model choice via random forests},
    author={Pudlo, Pierre and Marin, Jean-Michel and Estoup, Arnaud and Cornuet, Jean-Marie and Gautier, Mathieu and Robert, Christian P},
    journal={Bioinformatics},
    volume={32},
    number={6},
    pages={859--866},
    year={2016},
    publisher={Oxford University Press}
@article{Beaumont2019,
    title={Approximate Bayesian Computation},
    author={Beaumont, Mark A.},
    journal={Annual review of statistics and its application},
    volume={6},
    pages={379--403},
    year={2019},
    publisher={Annual Reviews}
@article{Beaumont2002,
    title={Approximate Bayesian computation in population genetics},
    author={Beaumont, Mark A. and Zhang, Wenyang and Balding, David J},
    journal={Genetics},
    volume={162},
    number={4},
    pages={2025--2035},
    year={2002},
    publisher={Oxford University Press}
@article{Beaumont2010,
    title={Approximate Bayesian computation in evolution and ecology},
    author={Beaumont, Mark A.},
    journal={Annual review of ecology, evolution, and systematics},
    volume={41},
    pages={379--406},
    year={2010},
    publisher={Annual Reviews}
@article{Lintusaari2018,
    title={Elfi: Engine for likelihood-free inference},
    author={Lintusaari, Jarno and Vuollekoski, Henri and Kangasraasio, Antti and Skyt{\'e}n, Kusti and Jarvenpaa, Marko and Marttinen, Pekka and Gutmann, Michael U and Vehtari, Aki and Corander, Jukka and Kaski, Samuel},
    journal={Journal of Machine Learning Research},
    volume={19},
    number={16},
    pages={1--7},
    year={2018}
@inproceedings{Dutta2017,
    title={ABCpy: A user-friendly, extensible, and parallel library for approximate Bayesian computation},
    author={Dutta, Ritabrata and Schoengens, Marcel and Onnela, Jukka-Pekka and Mira, Antonietta},
    booktitle={Proceedings of the platform for advanced scientific computing conference},
    pages={1--9},
    year={2017}
@article{Klinger2018,
    title={pyABC: distributed, likelihood-free inference},
    author={Klinger, Emmanuel and Rickert, Dennis and Hasenauer, Jan},
    journal={Bioinformatics},
    volume={34},
    number={20},
    pages={3591--3593},
    year={2018},
    publisher={Oxford University Press}
@Manual{PalmerPenguins,
    title = {palmerpenguins: Palmer Archipelago (Antarctica) penguin data},
    author = {Allison Marie Horst and Alison Presmanes Hill and Kristen B Gorman},
    year = {2020},
    note = {R package version 0.1.0},
    doi = {10.5281/zenodo.3960218},
    url = {https://allisonhorst.github.io/palmerpenguins/},
@inproceedings{gradient,
    title={Batch normalization: Accelerating deep network training by reducing internal covariate shift},
    author={Ioffe, Sergey and Szegedy, Christian},
    booktitle={International conference on machine learning},
    pages={448--456},
    year={2015},
    organization={PMLR}
@book{fox_fox_2016,
    title={Applied Regression Analysis and Generalized Linear Models},
    author={Fox, J.},
    isbn={9781483321318},
    year={2015},
    publisher={SAGE Publications}
@article{Robert2011,
    title={Lack of confidence in approximate Bayesian computation model choice},
    author={Robert, Christian P and Cornuet, Jean-Marie and Marin, Jean-Michel and Pillai, Natesh S},
    journal={Proceedings of the National Academy of Sciences},
    volume={108},
    number={37},
    pages={15112--15117},
    year={2011},
    publisher={National Acad Sciences}
    title={Regression and Other Stories},
    author={Gelman, A. and Hill, J. and Vehtari, A.},
    isbn={9781107023987},
    series={Analytical Methods for Social Research},
    year={2020},
    publisher={Cambridge University Press}
@article{LikehoodandPrior,
    title={The prior can often only be understood in the context of the likelihood},
    author={Gelman, Andrew and Simpson, Daniel and Betancourt, Michael},
    journal={Entropy},
    volume={19},
    number={10},
    pages={555},
    year={2017},
    publisher={Multidisciplinary Digital Publishing Institute}
@inproceedings{Collin2020,
    title={Bringing ABC inference to the machine learning realm: AbcRanger, an optimized random forests library for ABC},
    author={Collin, Fran{\c{c}}ois-David and Estoup, Arnaud and Marin, Jean-Michel and Raynal, Louis},
    booktitle={JOBIM 2020},
    volume={2020},
    year={2020}
@article{gorman_williams_fraser_2014,
    title={Ecological sexual dimorphism and environmental variability within a community of Antarctic penguins (genus Pygoscelis)},
    author={Gorman, Kristen B and Williams, Tony D and Fraser, William R},
    journal={PloS one},
    volume={9},
    number={3},
    pages={e90081},
    year={2014},
    publisher={Public Library of Science San Francisco, USA}
@article{Liu2020,
    title={Variable selection with ABC Bayesian forests},
    author={Liu, Yi and Ro{\v{c}}kov{\'a}, Veronika and Wang, Yuexi},
    journal={Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
    year={2019},
    publisher={Wiley Online Library}
@inproceedings{Rockova2018,
    title={On theory for BART},
    author={Ro{\v{c}}kov{\'a}, Veronika and Saha, Enakshi},
    booktitle={The 22nd International Conference on Artificial Intelligence and Statistics},
    pages={2839--2848},
    year={2019},
    organization={PMLR}
@book{martin_2018,
    title={Bayesian Analysis with Python: Introduction to Statistical Modeling and Probabilistic Programming Using PyMC3 and ArviZ, 2nd Edition},
    author={Martin, O.},
    isbn={9781789341652},
    year={2018},
    publisher={Packt Publishing}
@Manual{readingSkills,
    title = {Party: A laboratory for recursive partytioning},
    author = {Hothorn, Torsten and Hornik, Kurt and Strobl, Carolin and Zeileis, Achim},
    year = {2010},
    note = {R package version 1.3-7},
    url = {https://CRAN.R-project.org/package=party},
@article{Horiguchi2020,
    title={Assessing variable activity for Bayesian regression trees},
    author={Horiguchi, Akira and Pratola, Matthew T and Santner, Thomas J},
    journal={Reliability Engineering \& System Safety},
    volume={207},
    pages={107391},
    year={2021},
    publisher={Elsevier}
@article{Carlson2020,
    title={embarcadero: Species distribution modelling with Bayesian additive regression trees in R},
    author={Carlson, Colin J.},
    journal={Methods in Ecology and Evolution},
    volume={11},
    number={7},
    pages={850--858},
    year={2020},
    publisher={Wiley Online Library}
@article{Friedman2001,
    title={Greedy function approximation: a gradient boosting machine},
    author={Friedman, Jerome H},
    journal={Annals of statistics},
    pages={1189--1232},
    year={2001},
    publisher={JSTOR}
@article{Goldstein2014,
    title={Peeking inside the black box: Visualizing statistical learning with plots of individual conditional expectation},
    author={Goldstein, Alex and Kapelner, Adam and Bleich, Justin and Pitkin, Emil},
    journal={journal of Computational and Graphical Statistics},
    volume={24},
    number={1},
    pages={44--65},
    year={2015},
    publisher={Taylor \& Francis}
@inproceedings{Molnar2020,
    title={Interpretable machine learning--a brief history, state-of-the-art and challenges},
    author={Molnar, Christoph and Casalicchio, Giuseppe and Bischl, Bernd},
    booktitle={Joint European Conference on Machine Learning and Knowledge Discovery in Databases},
    pages={417--431},
    year={2020},
    organization={Springer}
@book{Molnarbook,
    title={Interpretable Machine Learning},
    author={Molnar, C.},
    isbn={9780244768522},
    year={2020},
    publisher={Lulu.com}
@article{Bleich2014,
    title={Variable selection for BART: an application to gene regulation},
    author={Bleich, Justin and Kapelner, Adam and George, Edward I and Jensen, Shane T},
    journal={The Annals of Applied Statistics},
    pages={1750--1781},
    year={2014},
    publisher={JSTOR}
@article{Sunnaker2013,
    title={Approximate bayesian computation},
    author={Sunn{\aa}ker, Mikael and Busetto, Alberto Giovanni and Numminen, Elina and Corander, Jukka and Foll, Matthieu and Dessimoz, Christophe},
    journal={PLoS computational biology},
    volume={9},
    number={1},
    pages={e1002803},
    year={2013},
    publisher={Public Library of Science San Francisco, USA}
@article{Gelman2020,
    title={Bayesian workflow},
    author={Gelman, Andrew and Vehtari, Aki and Simpson, Daniel and Margossian, Charles C and Carpenter, Bob and Yao, Yuling and Kennedy, Lauren and Gabry, Jonah and B{\"u}rkner, Paul-Christian and Modr{\'a}k, Martin},
    journal={arXiv preprint arXiv:2011.01808},
    year={2020}
@book{davidson-pilon_2015,
    title={Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference},
    author={Davidson-Pilon, C.},
    isbn={9780133902921},
    series={Addison-Wesley Data \& Analytics Series},
    year={2015},
    publisher={Pearson Education}
@article{gelman2005,
    title={Analysis of variance—why it is more important than ever},
    author={Gelman, Andrew},
    journal={The annals of statistics},
    volume={33},
    number={1},
    pages={1--53},
    year={2005},
    publisher={Institute of Mathematical Statistics}
@Manual{nlme,
    title = {{nlme}: Linear and Nonlinear Mixed Effects Models},
    author = {Jose Pinheiro and Douglas Bates and Saikat DebRoy and Deepayan Sarkar and {R Core Team}},
    year = {2020},
    note = {R package version 3.1-151},
    url = {https://CRAN.R-project.org/package=nlme},
@article{lme4,
    title={Fitting linear mixed-effects models using lme4},
    author={Bates, Douglas and M{\"a}chler, Martin and Bolker, Ben and Walker, Steve},
    journal={arXiv preprint arXiv:1406.5823},
    year={2014}
@misc{gabry_goodrich_2020, 
    title={Estimating Generalized (Non-)Linear Models with Group-Specific Terms with rstanarm},
    url={https://mc-stan.org/rstanarm/articles/glmer.html}, 
    author={Gabry, Jonah and Goodrich, Ben}, 
    year={2020}, 
    month={6}
@article{brms,
    title={brms: An R package for Bayesian multilevel models using Stan},
    author={B{\"u}rkner, Paul-Christian},
    journal={Journal of statistical software},
    volume={80},
    number={1},
    pages={1--28},
    year={2017}
@article{betancourt2013hamiltonian,
    title={Hamiltonian Monte Carlo for hierarchical models},
    author={Betancourt, Michael and Girolami, Mark},
    journal={Current trends in Bayesian methodology with applications},
    volume={79},
    number={30},
    pages={2--4},
    year={2015},
    publisher={CRC Press Boca Raton, FL}
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