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@Manual{rlang,
title = {R: A Language and Environment for Statistical Computing},
author = {{R Core Team}},
organization = {R Foundation for Statistical Computing},
address = {Vienna, Austria},
year = {2018},
url = {https://www.R-project.org/},
}
@Book{molnar2019,
title = {Interpretable Machine Learning},
author = {Christoph Molnar},
note = {\url{https://christophm.github.io/interpretable-ml-book/}},
year = {2019},
subtitle = {A Guide for Making Black Box Models Explainable}
}
@inproceedings{ribeiro2016should,
title={Why should i trust you?: Explaining the predictions of any classifier},
author={Ribeiro, Marco Tulio and Singh, Sameer and Guestrin, Carlos},
booktitle={Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining},
pages={1135--1144},
year={2016},
organization={ACM}
}
@misc{thomasp85lime,
author = {Pedersen, Thomas Lin},
title = {LIME R package},
year = {2019},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/thomasp85/lime}},
commit = {e86cb10d07edc8d2692e5661797bcbf2d4018f13}
}
@misc{marcotcrlime,
author = {Ribeiro, Marco Tulio Correia},
title = {LIME Python package},
year = {2019},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/marcotcr/lime}},
commit = {9415808bd7e1b7b0bf40fabfe7abed925f03cc14}
}
@article{2-1-missForest,
title = {MissForest - non-parametric missing value imputation for
mixed-type data},
author = {Daniel J. Stekhoven and Peter Buehlmann},
journal = {Bioinformatics},
volume = {28},
number = {1},
pages = {112--118},
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publisher = {Oxford Univ Press},
}
@article{2-1-VIM,
title = {Imputation with the {R} Package {VIM}},
author = {Alexander Kowarik and Matthias Templ},
journal = {Journal of Statistical Software},
year = {2016},
volume = {74},
number = {7},
pages = {1--16},
doi = {10.18637/jss.v074.i07},
}
@article{2-1-mice,
title = {{mice}: Multivariate Imputation by Chained Equations in
R},
author = {Stef {van Buuren} and Karin Groothuis-Oudshoorn},
journal = {Journal of Statistical Software},
year = {2011},
volume = {45},
number = {3},
pages = {1-67},
url = {https://www.jstatsoft.org/v45/i03/},
}
@article{2-1-caret,
author = {Max Kuhn},
title = {Building Predictive Models in R Using the caret Package},
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volume = {28},
number = {5},
year = {2008},
keywords = {},
abstract = {The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R. The package focuses on simplifying model training and tuning across a wide variety of modeling techniques. It also includes methods for pre-processing training data, calculating variable importance, and model visualizations. An example from computational chemistry is used to illustrate the functionality on a real data set and to benchmark the benefits of parallel processing with several types of models.},
issn = {1548-7660},
pages = {1--26},
doi = {10.18637/jss.v028.i05},
url = {https://www.jstatsoft.org/v028/i05}
}
@article{2-1-weighted-tpr-tnr,
author = {Jadhav, Anil},
year = {2020},
month = {03},
pages = {113391},
title = {A Novel Weighted TPR-TNR Measure to Assess Performance of the Classifiers},
volume = {152},
journal = {Expert Systems with Applications},
doi = {10.1016/j.eswa.2020.113391}
}
@book{2-1-little-rubin,
added-at = {2012-09-09T11:27:10.000+0200},
author = {Little, R.J.A. and Rubin, D.B.},
biburl = {https://www.bibsonomy.org/bibtex/2b2fb20df470898e82317fb855c088703/peter.ralph},
interhash = {3afe77a956d4d25ef971f22ee3172776},
intrahash = {b2fb20df470898e82317fb855c088703},
isbn = {9780471183860},
keywords = {missing_data statistics},
lccn = {2002027006},
publisher = {Wiley},
series = {Wiley series in probability and mathematical statistics. Probability and mathematical statistics},
timestamp = {2012-09-09T11:27:10.000+0200},
title = {Statistical analysis with missing data},
url = {http://books.google.com/books?id=aYPwAAAAMAAJ},
year = 2002
}
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title={Multivariate adaptive regression splines},
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publisher={Institute of Mathematical Statistics}
}
@Book{xie2015,
title = {Dynamic Documents with {R} and knitr},
author = {Yihui Xie},
publisher = {Chapman and Hall/CRC},
address = {Boca Raton, Florida},
year = {2015},
edition = {2nd},
note = {ISBN 978-1498716963},
url = {http://yihui.name/knitr/}
}
@article{breiman2001random,
title={Random forests},
author={Breiman, Leo},
journal={Machine learning},
volume={45},
number={1},
pages={5--32},
year={2001},
publisher={Springer}
}
@article{lei2018distribution,
title={Distribution-free predictive inference for regression},
author={Lei, Jing and G’Sell, Max and Rinaldo, Alessandro and Tibshirani, Ryan J and Wasserman, Larry},
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volume={113},
number={523},
pages={1094--1111},
year={2018},
publisher={Taylor \& Francis}
}
@article{fisher2018model,
title={Model Class Reliance: Variable importance measures for any machine learning model class, from the” Rashomon” perspective},
author={Fisher, Aaron and Rudin, Cynthia and Dominici, Francesca},
journal={arXiv preprint arXiv:1801.01489},
year={2018}
}
@misc{hall2017ideas,
title={Ideas on interpreting machine learning},
author={Hall, Patrick and Phan, Wen and Ambati, Sri Satish},
year={2017},
publisher={O’Reilly Ideas}
}
@article{molnar2018iml,
title={Iml: An r package for interpretable machine learning},
author={Molnar, Christoph and Casalicchio, Giuseppe and Bischl, Bernd},
journal={The Journal of Open Source Software},
volume={3},
number={786},
pages={10--21105},
year={2018}
}
@inproceedings{casalicchio2018visualizing,
title={Visualizing the feature importance for black box models},
author={Casalicchio, Giuseppe and Molnar, Christoph and Bischl, Bernd},
booktitle={Joint European Conference on Machine Learning and Knowledge Discovery in Databases},
pages={655--670},
year={2018},
organization={Springer}
}
@Book{Apley2016,
title = {Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models},
author = {Daniel W. Apley},
year = {2016},
url = {https://arxiv.org/ftp/arxiv/papers/1612/1612.08468.pdf},
}
@book{hastie2013elements,
title={The Elements of Statistical Learning: Data Mining, Inference, and Prediction},
author={Hastie, T. and Tibshirani, R. and Friedman, J.},
isbn={9780387216065},
lccn={2001031433},
series={Springer Series in Statistics},
url={https://books.google.de/books?id=yPfZBwAAQBAJ},
year={2013},
publisher={Springer New York}
}
@article{Goldstein2013,
author = {Goldstein, Alex and Kapelner, Adam and Bleich, Justin and Pitkin, Emil},
year = {2013},
month = {09},
pages = {},
title = {Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation},
volume = {24},
journal = {Journal of Computational and Graphical Statistics},
doi = {10.1080/10618600.2014.907095}
}
@article{laugel2018defining,
title={Defining locality for surrogates in post-hoc interpretablity},
author={Laugel, Thibault and Renard, Xavier and Lesot, Marie-Jeanne and Marsala, Christophe and Detyniecki, Marcin},
journal={arXiv preprint arXiv:1806.07498},
year={2018}
}
@inproceedings{craven1996,
title={Extracting tree-structured representations of trained networks},
author={Craven, Mark and Shavlik, Jude W},
booktitle={Advances in neural information processing systems},
pages={24--30},
year={1996}
}
@article{huang1998kproto,
title={Extensions to the k-means algorithm for clustering large data sets with categorical values},
author={Huang, Zhexue},
journal={Data mining and knowledge discovery},
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year={1998},
publisher={Springer}
}
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title={A general coefficient of similarity and some of its properties},
author={Gower, John C},
journal={Biometrics},
pages={857--871},
year={1971},
publisher={JSTOR}
}
@article{LIMEformula,
author = {Tomi Peltola},
title = {Local Interpretable Model-agnostic Explanations of Bayesian Predictive
Models via Kullback-Leibler Projections},
journal = {CoRR},
volume = {abs/1810.02678},
year = {2018},
url = {http://arxiv.org/abs/1810.02678},
archivePrefix = {arXiv},
eprint = {1810.02678},
timestamp = {Tue, 30 Oct 2018 10:49:09 +0100},
biburl = {https://dblp.org/rec/bib/journals/corr/abs-1810-02678},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{XGBoost,
author = {Tianqi Chen and
Carlos Guestrin},
title = {XGBoost: {A} Scalable Tree Boosting System},
journal = {CoRR},
volume = {abs/1603.02754},
year = {2016},
url = {http://arxiv.org/abs/1603.02754},
archivePrefix = {arXiv},
eprint = {1603.02754},
timestamp = {Mon, 13 Aug 2018 16:47:00 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/ChenG16},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{fanaee2014event,
title={Event labeling combining ensemble detectors and background knowledge},
author={Fanaee-T, Hadi and Gama, Joao},
journal={Progress in Artificial Intelligence},
volume={2},
number={2-3},
pages={113--127},
year={2014},
publisher={Springer}
}
@article{meinshausen2010stability,
title={Stability selection},
author={Meinshausen, Nicolai and B{\"u}hlmann, Peter},
journal={Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
volume={72},
number={4},
pages={417--473},
year={2010},
publisher={Wiley Online Library}
}
@article{alvarez2018robustness,
title={On the robustness of interpretability methods},
author={Alvarez-Melis, David and Jaakkola, Tommi S},
journal={arXiv preprint arXiv:1806.08049},
year={2018}
}
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author = {Strobl, Carolin and Boulesteix, Anne-Laure and Kneib, Thomas and Augustin, Thomas},
year = {2008},
month = {07},
pages = {},
title = {Conditional variable importance for random forest},
volume = {9},
journal = {BMC Bioinformatics},
doi = {10.1186/1471-2105-9-307}
}
@article{archer2008,
title={Empirical characterization of random forest variable importance measures},
author={Archer, Kellie J. and Kimes, Ryan V.},
journal={Computational Statistics and Data Analysis},
volume={52},
number={},
pages={2249-2260},
year={2008}
}
@article{parr2018,
title={Beware Default Random Forest Importances},
author={Parr, Terence and Turgutlu, Kerem and Csiszar, Christopher and Howard, Jeremy},
journal={},
volume={},
number={},
pages={},
url={https://explained.ai/rf-importance/index.html},
year={2018}
}
@article{hooker2019,
title={Please Stop Permuting Features: An Explanation and Alternatives},
author={Hooker, Giles and Mentch, Lucas},
journal={arXiv e-prints},
volume={},
number={},
pages={},
url={https://arxiv.org/pdf/1905.03151.pdf},
year={2019}
}
@article{harrison1978,
title={Hedonic prices and the demand for clean air},
author={Harrison, D. and Rubinfeld, D.L.},
journal={Economics and Management},
volume={5},
number={},
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url={},
year={1978}
}
@article{mentch2016,
title={Quantifying uncertainty in random forest via confidence intervals and hypothesis tests},
author={Mentch, Lucas and Hooker, Giles},
journal={The Journal of Maschine Learning Research},
volume={17},
number={1},
pages={841-881},
url={},
year={2016}
}
@Article{R-kernlab,
title = {kernlab -- An S4 Package for Kernel Methods in R},
author = {Alexandros Karatzoglou and Alex Smola and Kurt Hornik and
Achim Zeileis},
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year = {2004},
volume = {11},
number = {9},
pages = {1--20},
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}
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title={Comment: Graphical models, causality and intervention},
author={Pearl, Judea},
journal={Statistical Science},
volume={8},
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}
@Book{zhaohastie,
title = {Causal Interpretations of Black-Box Models},
author = {Zhao, Qingyuan and Hastie, Trevor},
year = {2018},
url = {http://web.stanford.edu/~hastie/Papers/pdp_zhao_final.pdf},
}
@misc{scholbeck,
title={Interpretierbares Machine-Learning.
Post-hoc modellagnostische Verfahren
zur Bestimmung von Prädiktoreffekten
in Supervised-Learning-Modellen},
author={Scholbeck, Christian},
year={2018},
publisher={Ludwig-Maximilians-Universität München}
}
@article{Fanaee-T,
year={2013},
issn={2192-6352},
journal={Progress in Artificial Intelligence},
doi={10.1007/s13748-013-0040-3},
title={Event labeling combining ensemble detectors and background knowledge},
url={[Web Link]},
publisher={Springer Berlin Heidelberg},
keywords={Event labeling; Event detection; Ensemble learning; Background knowledge},
author={Fanaee-T, Hadi and Gama, Joao},
pages={1-15}
}
@book{fahrmeir2016statistik,
title={Statistik: Der Weg zur Datenanalyse},
author={Fahrmeir, L. and Heumann, C. and K{\"u}nstler, R. and Pigeot, I. and Tutz, G.},
isbn={9783662503720},
series={Springer-Lehrbuch},
url={https://books.google.de/books?id=rKveDAAAQBAJ},
year={2016},
publisher={Springer Berlin Heidelberg}
}
@book{fahrmeir2013regression,
title={Regression: Models, Methods and Applications},
author={Fahrmeir, L. and Kneib, T. and Lang, S. and Marx, B.},
isbn={9783642343339},
url={https://books.google.de/books?id=EQxU9iJtipAC},
year={2013},
publisher={Springer Berlin Heidelberg}
}
@ARTICLE{2019arXiv190503151H,
author = {{Hooker}, Giles and {Mentch}, Lucas},
title = "{Please Stop Permuting Features: An Explanation and Alternatives}",
journal = {arXiv e-prints},
keywords = {Statistics - Methodology, Computer Science - Machine Learning, Statistics - Machine Learning, 62G08, I.5.1},
year = "2019",
month = "May",
eid = {arXiv:1905.03151},
pages = {arXiv:1905.03151},
archivePrefix = {arXiv},
eprint = {1905.03151},
primaryClass = {stat.ME},
adsurl = {https://ui.adsabs.harvard.edu/abs/2019arXiv190503151H},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{breiman2001,
author = "Breiman, Leo",
doi = "10.1214/ss/1009213726",
fjournal = "Statistical Science",
journal = "Statist. Sci.",
month = "08",
number = "3",
pages = "199--231",
publisher = "The Institute of Mathematical Statistics",
title = "Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)",
url = "https://doi.org/10.1214/ss/1009213726",
volume = "16",
year = "2001"
}
@article{ribeiro2016model,
title={Model-agnostic interpretability of machine learning},
author={Ribeiro, Marco Tulio and Singh, Sameer and Guestrin, Carlos},
journal={arXiv preprint arXiv:1606.05386},
year={2016}
}
@article{friedman2001greedy,
title={Greedy function approximation: a gradient boosting machine},
author={Friedman, Jerome H},
journal={Annals of statistics},
pages={1189--1232},
year={2001},
publisher={JSTOR}
}
@inproceedings{caruana2015intelligible,
title={Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission},
author={Caruana, Rich and Lou, Yin and Gehrke, Johannes and Koch, Paul and Sturm, Marc and Elhadad, Noemie},
booktitle={Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
pages={1721--1730},
year={2015},
organization={ACM}
}
@article {McNutt679,
author = {McNutt, Marcia},
title = {Journals unite for reproducibility},
volume = {346},
number = {6210},
pages = {679--679},
year = {2014},
doi = {10.1126/science.aaa1724},
publisher = {American Association for the Advancement of Science},
issn = {0036-8075},
URL = {https://science.sciencemag.org/content/346/6210/679},
eprint = {https://science.sciencemag.org/content/346/6210/679.full.pdf},
journal = {Science}
}
@article{Anda407,
author = {Anda, Bente and Sjøberg, Dag and Mockus, Audris},
year = {2009},
month = {07},
pages = {407 - 429},
title = {Variability and Reproducibility in Software Engineering: A Study of Four Companies that Developed the Same System},
volume = {35},
journal = {Software Engineering, IEEE Transactions on},
doi = {10.1109/TSE.2008.89}
}
@article {Peng1226,
author = {Peng, Roger D.},
title = {Reproducible Research in Computational Science},
volume = {334},
number = {6060},
pages = {1226--1227},
year = {2011},
doi = {10.1126/science.1213847},
publisher = {American Association for the Advancement of Science},
issn = {0036-8075},
URL = {https://science.sciencemag.org/content/334/6060/1226},
eprint = {https://pdfs.semanticscholar.org/2933/f511b94946e7dab4a8ba41c83b277dbf11a1.pdf},
journal = {Science}
}
@article {Patil066803,
author = {Patil, Prasad and Peng, Roger D. and Leek, Jeffrey T.},
title = {A statistical definition for reproducibility and replicability},
elocation-id = {066803},
year = {2016},
doi = {10.1101/066803},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2016/07/29/066803},
eprint = {https://www.biorxiv.org/content/early/2016/07/29/066803.full.pdf},
journal = {bioRxiv},
abstract = {Computational science has led to exciting new developments, but the nature of the work has exposed limitations in our ability to evaluate published findings. Reproducibility has the potential to serve as a minimum standard for judging scientific claims when full independent replication of a study is not possible.},
issn = {0036-8075},
URL = {https://science.sciencemag.org/content/334/6060/1226},
eprint = {https://science.sciencemag.org/content/334/6060/1226.full.pdf},
journal = {Science}
}
@inproceedings{Stodden2013SettingTD,
title={Setting the Default to Reproducible Reproducibility in Computational and Experimental Mathematics},
author={Victoria Stodden and David H. Bailey and Jonathan M. Borwein and Randall J. LeVeque and William J. Rider and William Stein},
year={2013}
}
@book{kitzes2017practice,
title={The practice of reproducible research: case studies and lessons from the data-intensive sciences},
author={Kitzes, Justin and Turek, Daniel and Deniz, Fatma},
year={2017},
publisher={Univ of California Press}
}
@misc{marwickrrtools,
title={rrtools: Creates a reproducible research compendium (2018)},
author={Marwick, B}
}
@article{gentleman2007statistical,
title={Statistical analyses and reproducible research},
author={Gentleman, Robert and Temple Lang, Duncan},
journal={Journal of Computational and Graphical Statistics},
volume={16},
number={1},
pages={1--23},
year={2007},
publisher={Taylor \& Francis}
}
@article{vandewalle2009reproducible,
title={Reproducible research in signal processing},
author={Vandewalle, Patrick and Kovacevic, Jelena and Vetterli, Martin},
journal={IEEE Signal Processing Magazine},
volume={26},
number={3},
pages={37--47},
year={2009},
publisher={IEEE}
}
@article{rosenberg2020the,
author = {David E. Rosenberg and Yves Filion and Rebecca Teasley and Samuel Sandoval-Solis and Jory S. Hecht and Jakobus E. van Zyl and George F. McMahon and Jeffery S. Horsburgh and Joseph R. Kasprzyk and David G. Tarboton },
title = {The Next Frontier: Making Research More Reproducible},
journal = {Journal of Water Resources Planning and Management},
volume = {146},
number = {6},
pages = {01820002},
year = {2020},
doi = {10.1061/(ASCE)WR.1943-5452.0001215},
URL = {https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29WR.1943-5452.0001215},
eprint = {https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29WR.1943-5452.0001215}
}
@article{leveque2009python,
author = {LeVeque, Randall},
year = {2009},
month = {01},
pages = {19-27},
title = {Python Tools for Reproducible Research on Hyperbolic Problems},
volume = {11},
journal = {Computing in Science & Engineering},
doi = {10.1109/MCSE.2009.13}
}
@article{stanisic2015an,
author = {Stanisic, Luka and Legrand, Arnaud and Danjean, Vincent},
title = {An Effective Git And Org-Mode Based Workflow For Reproducible Research},
year = {2015},
issue_date = {January 2015},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {49},
number = {1},
issn = {0163-5980},
url = {https://doi.org/10.1145/2723872.2723881},
doi = {10.1145/2723872.2723881},
journal = {SIGOPS Oper. Syst. Rev.},
month = jan,
pages = {61–70},
numpages = {10}
}
@article{fomel2013madagascar,
author = {Fomel, Sergey and Sava, Paul and Vlad, Ioan and Liu, Yang and Bashkardin, Vladimir},
year = {2013},
month = {11},
pages = {e8},
title = {Madagascar: Open-source software project for multidimensional data analysis and reproducible computational experiments},
volume = {1},
journal = {Journal of Open Research Software},
doi = {10.5334/jors.ag}
}
@article{hung2016guidock,
author = {Hung, Ling-Hong and Kristiyanto, Daniel and Lee, Sung and Yeung, Ka Yee},
year = {2016},
month = {04},
pages = {e0152686},
title = {GUIdock: Using Docker Containers with a Common Graphics User Interface to Address the Reproducibility of Research},
volume = {11},
journal = {PloS one},
doi = {10.1371/journal.pone.0152686}
}
@article{Goodman2016,
doi = {10.1126/scitranslmed.aaf5027},
url = {https://doi.org/10.1126/scitranslmed.aaf5027},
year = {2016},
month = jun,
publisher = {American Association for the Advancement of Science ({AAAS})},
volume = {8},
number = {341},
pages = {341ps12--341ps12},
author = {Steven N. Goodman and Daniele Fanelli and John P. A. Ioannidis},
title = {What does research reproducibility mean?},
journal = {Science Translational Medicine}
}
@article{Marwick2016,
doi = {10.1007/s10816-015-9272-9},
url = {https://doi.org/10.1007/s10816-015-9272-9},
year = {2016},
month = jan,
publisher = {Springer Science and Business Media {LLC}},
volume = {24},
number = {2},
pages = {424--450},
author = {Ben Marwick},
title = {Computational Reproducibility in Archaeological Research: Basic Principles and a Case Study of Their Implementation},
journal = {Journal of Archaeological Method and Theory}
}
@article{Piccolo2016,
doi = {10.1186/s13742-016-0135-4},
url = {https://doi.org/10.1186/s13742-016-0135-4},
year = {2016},
month = jul,
publisher = {Oxford University Press ({OUP})},
volume = {5},
number = {1},
author = {Stephen R. Piccolo and Michael B. Frampton},
title = {Tools and techniques for computational reproducibility},
journal = {{GigaScience}}
}
@article{Piccolo2016,
doi = {10.1186/s13742-016-0135-4},
url = {https://doi.org/10.1186/s13742-016-0135-4},
year = {2016},
month = jul,
publisher = {Oxford University Press ({OUP})},
volume = {5},
number = {1},
author = {Stephen R. Piccolo and Michael B. Frampton},
title = {Tools and techniques for computational reproducibility},
journal = {{GigaScience}}
}
@article{Kluyver2016,
title = {Jupyter Notebooks – a publishing format for reproducible computational workflows},
volume = {0},
ISSN = {0000-0000},
url = {http://doi.org/10.3233/978-1-61499-649-1-87},
DOI = {10.3233/978-1-61499-649-1-87},
number = {Positioning and Power in Academic Publishing: Players, Agents and Agendas},
journal = {Stand Alone},
publisher = {IOS Press},
author = {Kluyver Thomas and Ragan-Kelley Benjamin and Pérez Fernando and Granger Brian and Bussonnier Matthias and Frederic Jonathan and Kelley Kyle and Hamrick Jessica and Grout Jason and Corlay Sylvain and et al.},
year = {2016},
pages = {87–90}
}
@article{Marwick2017,
doi = {10.1080/00031305.2017.1375986},
url = {https://doi.org/10.1080/00031305.2017.1375986},
year = {2017},
month = sep,
publisher = {Informa {UK} Limited},
volume = {72},
number = {1},
pages = {80--88},
author = {Ben Marwick and Carl Boettiger and Lincoln Mullen},
title = {Packaging Data Analytical Work Reproducibly Using R (and Friends)},
journal = {The American Statistician}
}
@article{Fernndez2019OpenSI,
title={Open Science in Software Engineering},
author={Daniel M{\'e}ndez Fern{\'a}ndez and Daniel Graziotin and Stefan Wagner and Heidi Seibold},
journal={ArXiv},
year={2019},
volume={abs/1904.06499}
}
@inproceedings{Raff2019AST,
title={A Step Toward Quantifying Independently Reproducible Machine Learning Research},
author={Edward Raff},
booktitle={NeurIPS},
year={2019}
}
@article{article,
author = {Vandewalle, Patrick and Kovacevic, Jelena and Vetterli, Martin},
year = {2009},
month = {06},
pages = {37 - 47},
title = {Reproducible Research in Signal Processing},
volume = {26},
journal = {Signal Processing Magazine, IEEE},
doi = {10.1109/MSP.2009.932122}
}
@article{Eisner2018,
doi = {10.1016/j.yjmcc.2017.10.009},
url = {https://doi.org/10.1016/j.yjmcc.2017.10.009},
year = {2018},
month = jan,
publisher = {Elsevier {BV}},
volume = {114},
pages = {364--368},
author = {D.A. Eisner},
title = {Reproducibility of science: Fraud, impact factors and carelessness},
journal = {Journal of Molecular and Cellular Cardiology}
}
@article{McNutt679,
author = {McNutt, Marcia},
title = {Journals unite for reproducibility},
volume = {346},
number = {6210},
pages = {679--679},
year = {2014},
doi = {10.1126/science.aaa1724},
publisher = {American Association for the Advancement of Science},
issn = {0036-8075},
URL = {https://science.sciencemag.org/content/346/6210/679},
eprint = {https://science.sciencemag.org/content/346/6210/679.full.pdf},
journal = {Science}
}
@article{Stodden2584,
author = {Stodden, Victoria and Seiler, Jennifer and Ma, Zhaokun},
title = {An empirical analysis of journal policy effectiveness for computational reproducibility},
volume = {115},
number = {11},
pages = {2584--2589},
year = {2018},
doi = {10.1073/pnas.1708290115},
publisher = {National Academy of Sciences},
abstract = {A key component of scientific communication is sufficient information for other researchers in the field to reproduce published findings. For computational and data-enabled research, this has often been interpreted to mean making available the raw data from which results were generated, the computer code that generated the findings, and any additional information needed such as workflows and input parameters. Many journals are revising author guidelines to include data and code availability. This work evaluates the effectiveness of journal policy that requires the data and code necessary for reproducibility be made available postpublication by the authors upon request. We assess the effectiveness of such a policy by (i) requesting data and code from authors and (ii) attempting replication of the published findings. We chose a random sample of 204 scientific papers published in the journal Science after the implementation of their policy in February 2011. We found that we were able to obtain artifacts from 44\% of our sample and were able to reproduce the findings for 26\%. We find this policy{\textemdash}author remission of data and code postpublication upon request{\textemdash}an improvement over no policy, but currently insufficient for reproducibility.},
issn = {0027-8424},
URL = {https://www.pnas.org/content/115/11/2584},
eprint = {https://www.pnas.org/content/115/11/2584.full.pdf},
journal = {Proceedings of the National Academy of Sciences}
}
@article{Elmenreich2018,
doi = {10.7287/peerj.preprints.27082v1},
url = {https://doi.org/10.7287/peerj.preprints.27082v1},
year = {2018},
month = aug,
publisher = {{PeerJ}},
author = {Wilfried Elmenreich and Philipp Moll and Sebastian Theuermann and Mathias Lux},
title = {Making computer science results reproducible - A case study using Gradle and Docker}
}
@article{Stodden1240,
author = {Stodden, Victoria and McNutt, Marcia and Bailey, David H. and Deelman, Ewa and Gil, Yolanda and Hanson, Brooks and Heroux, Michael A. and Ioannidis, John P.A. and Taufer, Michela},
title = {Enhancing reproducibility for computational methods},
volume = {354},
number = {6317},
pages = {1240--1241},
year = {2016},
doi = {10.1126/science.aah6168},
publisher = {American Association for the Advancement of Science},
issn = {0036-8075},
URL = {https://science.sciencemag.org/content/354/6317/1240},
eprint = {https://science.sciencemag.org/content/354/6317/1240.full.pdf},
journal = {Science}
}
@article{Ezcuj,
doi = {10.17605/OSF.IO/EZCUJ},
url = {https://osf.io/ezcuj/},
author = {Anderson, Christopher and Anderson, Joanna and van Assen, Marcel and Attridge, Peter and Attwood, Angela and Axt, Jordan and Babel, Molly and Bahník, Štěpán and Baranski, Erica and Barnett-Cowan, Michael and Bartmess, Elizabeth and Beer, Jennifer and Bell, Raoul and Bentley, Heather and van den Bergh, Don and Beyan, Leah and den Bezemer, Bobby and Borsboom, Denny and Bosch, Annick and Bosco, Frank and Bowman, Sara and Brandt, Mark and Braswell, Erin and Brohmer, Hilmar and Brown, Benjamin and Brown, Kristina and Br\"{u}ning, Jovita and Calhoun-Sauls, Ann and Callahan, Shannon and Chagnon, Elizabeth and Chandler, Jesse and Chartier, Christopher and Cheung, Felix and Chu, Phuonguyen and Cillessen, Linda and Clay, Russ and Cleary, Hayley and Cloud, Mark and Cohn, Michael and Cohoon, Johanna and Columbus, Simon and Costantini, Giulio and Cramblet Alvarez, Leslie and Cremata, Edward and Crusius, Jan and DeCoster, Jamie and DeGaetano, Michelle and Della Penna, Nicolás and Deserno, Marie and Devitt, Olivia and Dewitte, Laura and DiGiacomo, Philip and Dobolyi, David and Dodson, Geneva and Donnellan, Brent and Donohue, Ryan and van Dooren, Roel and van Doorn, Johnny and Dore, Rebecca and Dorrough, Angela and Dorsthorst, Anniek and Dreber, Anna and Dugas, Michelle and Dunn, Elizabeth and Easey, Kayleigh and Eboigbe, Sylvia and Eggleston, Casey and Embley, Jo and Epskamp, Sacha and Errington, Timothy and Estel, Vivien and Farach, Frank and Feather, Jenelle and Fedor, Anna and Fernández, Belén and Fiedler, Susann and Field, James and Fitneva, Stanka and Flagan, Taru and Forest, Amanda and Forsell, Eskil and Foster, Joshua and Frank, Michael and Frazier, Rebecca and Fuchs, Heather and Gable, Philip and Galak, Jeff and Galliani, Elisa and Gampa, Anup and Garcia, Sara and Gazarian, Douglas and Gilbert, Elizabeth and Giner-Sorolla, Roger and Gl\"{o}ckner, Andreas and Goellner, Lars and Goh, Jin and Goldberg, Rebecca and Goldinger, Stephen and Goodbourn, Patrick and Gordon-McKeon, Shauna and Gorges, Bryan and Gorges, Jessie and Goss, Justin and Graham, Jesse and Gray, Jeremy and Hartgerink, Chris and Hasselman, Fred and Hayes, Timothy and Heikensten, Emma and Henninger, Felix and Hicks, Grace and Hodsoll, John and Holubar, Taylor and Hoogendoorn, Geertje and van der Hulst, Marije and Humphries, Denise and Hung, Cathy and Immelman, Nathali and Irsik, Vanessa and Jahn, Georg and J\"{a}kel, Frank and Jekel, Marc and Johannesson, Magnus and Johnson, David and Johnson-Grey, Kate and Johnson, Larissa and Johnston, William and Jonas, Kai and Joy-Gaba, Jennifer and Kappes, Heather and Kelso, Kim and Kidwell, Mallory and Kim, Seung and Kirkhart, Matthew and Kleinberg, Bennett and Knezevic, Goran and Kolorz, Franziska and Krause, Robert and Krijnen, Job and Kuhlmann, Tim and Kunkels, Yoram and Kyc, Megan and Lai, Calvin and Laique, Aamir and Lakens, Daniel and Lane, Kristin and Lassetter, Bethany and Lazarevic, Ljiljana and LeBel, Etienne and Lee, Key Jung and Lee, Minha and Lemm, Kristi and Levitan, Carmel and Lewis, Melissa and Lin, Lin and Lin, Stephanie and Lippold, Matthias and Loureiro, Darren and Lumian, Daniel and Luteijn, Ilse and Mackinnon, Sean and Mainard, Heather and Marigold, Denise and Martin, Daniel and Martinez, Tylar and Masicampo, E.J. and Matacotta, Joshua and Mathur, Maya and May, Michael and McRae, Kateri and McElroy, Todd and Mechin, Nicole and Mehta, Pranjal and Meixner, Johannes and Melinger, Alissa and Miller, Jeremy and Smith, Mallorie and Moore, Katherine and M\"{o}schl, Marcus and Motyl, Matt and M\"{u}ller, Stephanie and Munafo, Marcus and Muñoz, Alisa and Neijenhuijs, Koen and Nervi, Taylor and Nicolas, Gandalf and Nilsonne, Gustav and Nosek, Brian and Olsson, Catherine and Osborne, Colleen and Ostkamp, Lutz and Pavel, Misha and Perna, Olivia and Pernet, Cyril and Perugini, Marco and Pipitone, R. Nathan and Pitts, Michael and Plessow, Franziska and Prenoveau, Jason and Ratliff, Kate and Reinhard, David and Renkewitz, Frank and van Renswoude, Daan and Ricker, Ashley and Rigney, Anastasia and van Rijn, Hedderik and Rivers, Andrew and Roebke, Mark and Rutchick, Abraham and Ryan, Robert and Sahin, Onur and Saide, Anondah and Sandstrom, Gillian and Santos, David and Saxe, Rebecca and Schlegelmilch, René and Schmidt, Kathleen and Scholz, Sabine and Seibel, Larissa and Selterman, Dylan and Shaki, Samuel and Simpson, William and Sinclair, H. and Skorinko, Jeanine and Slowik, Agnieszka and Snyder, Joel and Soderberg, Courtney and Sonnleitner, Carina and Spencer, Nicholas and Spies, Jeffrey and Staples, Angela and steegen, sara and Steinberg, Mia and Stieger, Stefan and Strohminger, Nina and Sullivan, Gavin and Talhelm, Thomas and Tapia, Megan and Thomae, Manuela and Toton, Sarah and Tibboel, Helen and Tio, Pia and Traets, Frits and Tsang, Steve and Tuerlinckx, Francis and Tullett, Alexa and Turchan, Paul and vanpaemel, wolf and Vásquez Echeverría, Alejandro and van 't Veer, Anna and Vélez, Natalia and van de Ven, Mathijs and Vermue, Marieke and Verschoor, Mark and Vianello, Michelangelo and Voracek, Martin and Vuu, Gina and Wagenmakers, Eric-Jan and Weerdmeester, Johanna and Welsh, Ashlee and Westgate, Erin and Wissink, Joeri and Wood, Michael and {, Andy} and Wright, Emily and Wu, Sining and Zeelenberg, Marcel and Zuni, Kellylynn and Hartshorne, Joshua and Grange, Jim},
title = {Reproducibility Project: Psychology},
publisher = {Open Science Framework},
year = {2019}
}
@inbook{Drummond2012,
author = {Drummond, Chris},
year = {2012},
month = {12},
pages = {},
title = {Reproducible Research: a Dissenting Opinion}
}
@paper{AAAI1817248,
author = {Odd Erik Gundersen and Sigbjørn Kjensmo},
title = {State of the Art: Reproducibility in Artificial Intelligence},
conference = {AAAI Conference on Artificial Intelligence},
year = {2018},
keywords = {empirical research; reproducible research; research method; documentation},
url = {https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17248}
}
@article{Archivist,
title = {{archivist}: An {R} Package for Managing, Recording and
Restoring Data Analysis Results},
author = {Przemyslaw Biecek and Marcin Kosinski},
journal = {Journal of Statistical Software},
year = {2017},
volume = {82},
number = {11},
pages = {1--28},
doi = {10.18637/jss.v082.i11},
}
@article{SlezakWaczulikova2011,
author = {Slezak, Peter and Waczulikova, Iveta},
year = {2011},
month = {04},
pages = {203-4; author reply 204},
title = {Reproducibility and Repeatability},
volume = {60},
journal = {Physiological research / Academia Scientiarum Bohemoslovaca}
}
@misc{JournalMetrics,
title = {Journal metrics - Impact, Speed and Reach},
howpublished = {\url{https://www.journals.elsevier.com/international-journal-of-approximate-reasoning/news/journal-metricsimpact-speed-and-reach}},
note = {\url{https://www.journals.elsevier.com/international-journal-of-approximate-reasoning/news/journal-metricsimpact-speed-and-reach},
Last accessed on 21.04.2020}
}
@article{ade4,
author = {Stéphane Dray and Anne-Béatrice Dufour},
title = {The ade4 Package: Implementing the Duality Diagram for Ecologists},
journal = {Journal of Statistical Software, Articles},
volume = {22},
number = {4},
year = {2007},
issn = {1548-7660},
pages = {1--20},
doi = {10.18637/jss.v022.i04},
url = {https://www.jstatsoft.org/v022/i04}
}
@article{untb,
author = {Robin Hankin},
title = {Introducing untb, an R Package For Simulating Ecological Drift Under the Unified Neutral Theory of Biodiversity},
journal = {Journal of Statistical Software, Articles},
volume = {22},
number = {12},
year = {2007},
issn = {1548-7660},
pages = {1--15},
doi = {10.18637/jss.v022.i12},
url = {https://www.jstatsoft.org/v022/i12}
}
@article{bio,
author = {Lester Yuan},
title = {Maximum Likelihood Method for Predicting Environmental Conditions from Assemblage Composition: The R Package bio.infer},
journal = {Journal of Statistical Software, Articles},
volume = {22},
number = {3},
year = {2007},
issn = {1548-7660},
pages = {1--20},
doi = {10.18637/jss.v022.i03},
url = {https://www.jstatsoft.org/v022/i03}
}
@article{pls,
author = {Björn-Helge Mevik and Ron Wehrens},
title = {The pls Package: Principal Component and Partial Least Squares Regression in R},
journal = {Journal of Statistical Software, Articles},
volume = {18},
number = {2},
year = {2007},
issn = {1548-7660},
pages = {1--23},
doi = {10.18637/jss.v018.i02},
url = {https://www.jstatsoft.org/v018/i02}
}
@article{EMD,
author = {Donghoh Kim and Hee-Seok Oh},
title = {{EMD: A Package for Empirical Mode Decomposition and Hilbert
Spectrum}},
year = {2009},
journal = {{The R Journal}},
doi = {10.32614/RJ-2009-002},
url = {https://doi.org/10.32614/RJ-2009-002},
pages = {40--46},
volume = {1},
number = {1}
}
@article{admit,
author = {David Ardia and Lennart F. Hoogerheide and Herman K. van
Dijk},
title = {{AdMit}},
year = {2009},
journal = {{The R Journal}},
doi = {10.32614/RJ-2009-003},
url = {https://doi.org/10.32614/RJ-2009-003},
pages = {25--30},
volume = {1},
number = {1}
}
@article{mvtnorm,
author = {Xuefei Mi and Tetsuhisa Miwa and Torsten Hothorn},
title = {{New Numerical Algorithm for Multivariate Normal
Probabilities in Package mvtnorm}},
year = {2009},
journal = {{The R Journal}},
doi = {10.32614/RJ-2009-001},
url = {https://doi.org/10.32614/RJ-2009-001},
pages = {37--39},
volume = {1},
number = {1}
}
@article{tmvtnorm,
author = {Stefan Wilhelm and B. G. Manjunath},
title = {{tmvtnorm: A Package for the Truncated Multivariate Normal
Distribution}},
year = {2010},
journal = {{The R Journal}},
doi = {10.32614/RJ-2010-005},
url = {https://doi.org/10.32614/RJ-2010-005},