R package Hmisc: Harrell Miscellaneous , The Hmisc library contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of S objects to LaTeX code, and recoding variables. Please submit bug reports to ’’. (Source:

References in zbMATH (referenced in 41 articles )

Showing results 21 to 40 of 41.
Sorted by year (citations)
  1. Heiberger, Richard M.; Holland, Burt: Statistical analysis and data display. An intermediate course with examples in R (2015)
  2. Pierre Bunouf; Geert Molenberghs; Jean-Marie Grouin; Herbert Thijs: A SAS Program Combining R Functionalities to Implement Pattern-Mixture Models (2015) not zbMATH
  3. Scott Fortmann-Roe: Consistent and Clear Reporting of Results from Diverse Modeling Techniques: The A3 Method (2015) not zbMATH
  4. Xiaoyue Cheng and Dianne Cook and Heike Hofmann: Visually Exploring Missing Values in Multivariable Data Using a Graphical User Interface (2015) not zbMATH
  5. Gruber, Susan; Van der Laan, Mark J.: An application of targeted maximum likelihood estimation to the meta-analysis of safety data (2013)
  6. Kuhn, Max; Johnson, Kjell: Applied predictive modeling (2013)
  7. Wollschläger, Daniel: R compact. The fast introduction into data analysis (2013)
  8. Broström, Göran: Event history analysis with R (2012)
  9. Cano, Emilio L.; Moguerza, Javier M.; Redchuk, Andrés: Six Sigma with R. Statistical engineering for process improvement. (2012)
  10. Ulla Mogensen; Hemant Ishwaran; Thomas Gerds: Evaluating Random Forests for Survival Analysis Using Prediction Error Curves (2012) not zbMATH
  11. Abrahantes, José Cortiñas; Sotto, Cristina; Molenberghs, Geert; Vromman, Geert; Bierinckx, Bart: A comparison of various software tools for dealing with missing data via imputation (2011)
  12. Recai Yucel: State of the Multiple Imputation Software (2011) not zbMATH
  13. Williams, Graham: Data Mining with Rattle and R. The art of excavating data for knowledge discovery. (2011)
  14. Kojadinovic, Ivan: Hierarchical clustering of continuous variables based on the empirical copula process and permutation linkages (2010)
  15. Wollschläger, Daniel: Foundations of data analysis with R. An application oriented introduction. (2010)
  16. Ambrogi, Federico; Biganzoli, Elia; Boracchi, Patrizia: Estimating crude cumulative incidences through multinomial logit regression on discrete cause-specific hazards (2009)
  17. Juned Siddique; Ofer Harel: MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors (2009) not zbMATH
  18. Péter Sólymos: Processing Ecological Data in R with the mefa Package (2009) not zbMATH
  19. Ryan Admiraal; Mark Handcock: networksis: A Package to Simulate Bipartite Graphs with Fixed Marginals Through Sequential Importance Sampling (2008) not zbMATH
  20. Ambrogi, Federico; Lama, Nicola; Boracchi, Patrizia; Biganzoli, Elia: Selection of artificial neural network models for survival analysis with genetic algorithms (2007)