CRAN

R is ‘GNU S’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. Please consult the R project homepage for further information. CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R. Please use the CRAN mirror nearest to you to minimize network load

Keywords for this software

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References in zbMATH (referenced in 432 articles , 1 standard article )

Showing results 1 to 20 of 432.
Sorted by year (citations)

1 2 3 ... 20 21 22 next

  1. Annarosa Quarello, Olivier Bock, Emilie Lebarbier: A new segmentation method for the homogenisation of GNSS-derived IWV time-series (2020) arXiv
  2. Benjamin G. Stokell, Rajen D. Shah, Ryan J. Tibshirani: Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties (2020) arXiv
  3. Bob Obenchain: Ridge TRACE Diagnostics (2020) arXiv
  4. Bradley C. Saul, Michael G. Hudgens: The Calculus of M-Estimation in R with geex (2020) not zbMATH
  5. Chainarong Amornbunchornvej: mFLICA: An R package for Inferring Leadership of Coordination From Time Series (2020) arXiv
  6. David B. Dahl: Integration of R and Scala Using rscala (2020) not zbMATH
  7. de Castro, Mário; Gómez, Yolanda M.: A Bayesian cure rate model based on the power piecewise exponential distribution (2020)
  8. Ducharme, Gilles R.; Lafaye de Micheaux, Pierre: A goodness-of-fit test for elliptical distributions with diagnostic capabilities (2020)
  9. Fabrizi, Enrico; Salvati, Nicola; Trivisano, Carlo: Robust Bayesian small area estimation based on quantile regression (2020)
  10. F. Aragón-Royón, A. Jiménez-Vílchez, A. Arauzo-Azofra, J. M. Benítez: FSinR: an exhaustive package for feature selection (2020) arXiv
  11. Felipe Campelo, Lucas Batista, Claus Aranha: The MOEADr Package: A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition (2020) not zbMATH
  12. Gaigall, Daniel: Testing marginal homogeneity of a continuous bivariate distribution with possibly incomplete paired data (2020)
  13. Gero Szepannek: An Overview on the Landscape of R Packages for Credit Scoring (2020) arXiv
  14. Grundy, Thomas; Killick, Rebecca; Mihaylov, Gueorgui: High-dimensional changepoint detection via a geometrically inspired mapping (2020)
  15. Haddon, Malcolm: Using R for modelling and quantitative methods in fisheries (2020)
  16. Hao Wang, Diederick Vermetten, Carola Doerr, Thomas Bäck: IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic (2020) arXiv
  17. Hu, Chaoran; Pozdnyakov, Vladimir; Yan, Jun: Density and distribution evaluation for convolution of independent gamma variables (2020)
  18. Imani, Mahdi; Dougherty, Edward R.; Braga-Neto, Ulisses: Boolean Kalman filter and smoother under model uncertainty (2020)
  19. Karolos K. Korkas: Ensemble Binary Segmentation for irregularly spaced data with change-points (2020) arXiv
  20. Kisung You, Changhee Suh: Rdimtools: An R package for Dimension Reduction and Intrinsic Dimension Estimation (2020) arXiv

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Further publications can be found at: http://journal.r-project.org/