Paper corpus

The following articles and ERCs have been created by the o2r team to demonstrate the feasibility and features of the o2r reproducibility service and platform.

• Bolin D, Frigessi A, Guttorp P, Haug O, Orskaug E, Scheel I and Wallin J (2016), “Calibrating regionally downscaled precipitation over Norway through quantile-based approaches”, Advances in Statistical Climatology, Meteorology and Oceanography. Vol. 2(1), pp. 39-47.
  DOI: http://doi.org/10.5194/ascmo-2-39-2016
  ERC: https://o2r.uni-muenster.de/#!/erc/czPWq
• Bond-Lamberty B, Smith AP and Bailey V (2016), “Temperature and moisture effects on greenhouse gas emissions from deep active-layer boreal soils”, Biogeosciences. Vol. 13(24), pp. 6669-6681.
  DOI: http://doi.org/10.5194/bg-13-6669-2016
  ERC: https://o2r.uni-muenster.de/#!/erc/8s9bP
• van Buuren S and Groothuis-Oudshoorn K (2011), “mice: Multivariate Imputation by Chained Equations in R”, Journal of Statistical Software. Vol. 45(3) Foundation for Open Access Statistic.
  DOI: http://doi.org/10.18637/jss.v045.i03
  ERC: https://o2r.uni-muenster.de/#!/erc/wu5C7
• Dottori F, Figueiredo R, Martina MLV, Molinari D and Scorzini AR (2016), “INSYDE: a synthetic, probabilistic flood damage model based on explicit cost analysis”, Natural Hazards and Earth System Sciences., dec, 2016. Vol. 16(12), pp. 2577-2591.
  DOI: http://doi.org/10.5194/nhess-16-2577-2016
  ERC: https://o2r.uni-muenster.de/#!/erc/5LVlQ
• Fan Y, Olson R and Evans JP (2017), “A Bayesian posterior predictive framework for weighting ensemble regional climate models”, Geoscientific Model Development., jun, 2017. Vol. 10(6), pp. 2321-2332.
  DOI: http://doi.org/10.5194/gmd-10-2321-2017
  ERC: https://o2r.uni-muenster.de/#!/erc/5F7FV
• Fraza E, Elsner JB and Jagger TH (2016), “A space–time statistical climate model for hurricane intensification in the North Atlantic basin”, Advances in Statistical Climatology, Meteorology and Oceanography. Vol. 2(2), pp. 105-114.
  DOI: http://doi.org/10.5194/ascmo-2-105-2016
  ERC: https://o2r.uni-muenster.de/#!/erc/onYGX
• Grolemund G and Wickham H (2011), “Dates and Times Made Easy with lubridate”, Journal of Statistical Software, Articles. Vol. 40(3), pp. 1-25.
  DOI: https://doi.org/10.18637/jss.v040.i03
  ERC: https://o2r.uni-muenster.de/#!/erc/2HXy2
• Khomo L, Trumbore S, Bern CR and Chadwick OA (2017), “Timescales of carbon turnover in soils with mixed crystalline mineralogies”, SOIL., jan, 2017. Vol. 3(1), pp. 17-30.
  DOI: http://doi.org/10.5194/soil-3-17-2017
  ERC: https://o2r.uni-muenster.de/#!/erc/k4LY5
• Niculiţa M (2016), “Automatic landslide length and width estimation based on the geometric processing of the bounding box and the geomorphometric analysis of DEMs”, Natural Hazards and Earth System Sciences. Vol. 16(8), pp. 2021-2030.
  DOI: http://doi.org/10.5194/nhess-16-2021-2016
  ERC: https://o2r.uni-muenster.de/#!/erc/hGNAf
• Pebesma E (2012), “spacetime: Spatio-Temporal Data in R”, Journal of Statistical Software, Articles. Vol. 51(7), pp. 1-30.
  DOI: http://doi.org/10.18637/jss.v051.i07
  ERC: https://o2r.uni-muenster.de/#!/erc/sNeVK
• van Noordwijk M, Tanika L and Lusiana B (2017), “Flood risk reduction and flow buffering as ecosystem services–Part 1: Theory on flow persistence, flashiness and base flow”, Hydrology and Earth System Sciences., May, 2017. Vol. 21(5), pp. 2321-2340.
  DOI: http://doi.org/10.5194/hess-21-2321-2017
  ERC: https://o2r.uni-muenster.de/#!/erc/mV2bs
• Thomas L and Reyes E (2014), “Tutorial: Survival Estimation for Cox Regression Models with Time-Varying Coefficients Using SAS and R”, Journal of Statistical Software, Code Snippets. Vol. 61(1), pp. 1-23.
  DOI: http://doi.org/10.18637/jss.v061.c01
  ERC: https://o2r.uni-muenster.de/#!/erc/EihH5
• Trachsel M and Telford RJ (2016), “Technical note: Estimating unbiased transfer-function performances in spatially structured environments”, Climate of the Past., May, 2016. Vol. 12, pp. 1215-1223.
  DOI: http://doi.org/10.5194/cp-12-1215-2016
  ERC: https://o2r.uni-muenster.de/#!/erc/SDFEv
• Viechtbauer W (2010), “Conducting Meta-Analyses in R with the metafor Package”, Journal of Statistical Software, Articles. Vol. 36(3), pp. 1-48.
  DOI: http://doi.org/10.18637/jss.v036.i03
  ERC: https://o2r.uni-muenster.de/#!/erc/djvve
• Wickham H (2011), “The Split-Apply-Combine Strategy for Data Analysis”, Journal of Statistical Software. Vol. 40(1).
  DOI: http://doi.org/10.18637/jss.v040.i01
  ERC: https://o2r.uni-muenster.de/#!/erc/sPprl
• Wickham H (2014), “Tidy data”, The Journal of Statistical Software. Vol. 59
  DOI: https://doi.org/10.18637/jss.v059.i10
  ERC: https://o2r.uni-muenster.de/#!/erc/N4Jzp