References in zbMATH (referenced in 15 articles )

Showing results 1 to 15 of 15.
Sorted by year (citations)

  1. Betsch, Steffen; Ebner, Bruno: Testing normality via a distributional fixed point property in the Stein characterization (2020)
  2. Izhar Asael Alonzo Matamoros, Alicia Nieto-Reyes: An R package for Normality in Stationary Processes (2020) arXiv
  3. Sánchez-Espigares, José A.; Grima, Pere; Marco-Almagro, Lluís: Graphical comparison of normality tests for unimodal distribution data (2019)
  4. Alicja Gosiewska; Przemyslaw Biecek: auditor: an R Package for Model-Agnostic Visual Validation and Diagnostic (2018) arXiv
  5. Duller, Christine: Introduction to nonparametric statistics with SAS, R and SPSS. An application-oriented text and working book (2018)
  6. González-Estrada, E.; Villaseñor, J. A.: An R package for testing goodness of fit: goft (2018)
  7. Pierre Lafaye de Micheaux and Viet Tran: PoweR: A Reproducible Research Tool to Ease Monte Carlo Power Simulation Studies for Goodness-of-fit Tests in R (2016) not zbMATH
  8. Stojanović, Vladica S.; Popović, Biljana Č.; Milovanović, Gradimir V.: The Split-SV model (2016)
  9. Ugarte, María Dolores; Militino, Ana F.; Arnholt, Alan T.: Probability and statistics with R (2016)
  10. Joenssen, Dieter W.; Vogel, Jürgen: A power study of goodness-of-fit tests for multivariate normality implemented in R (2014)
  11. Jeffrey Miecznikowski; Albert Vexler; Lori Shepherd: dbEmpLikeGOF: An R Package for Nonparametric Likelihood Ratio Tests for Goodness-of-Fit and Two-Sample Comparisons Based on Sample Entropy (2013) not zbMATH
  12. Wollschläger, Daniel: R compact. The fast introduction into data analysis (2013)
  13. Cano, Emilio L.; Moguerza, Javier M.; Redchuk, Andrés: Six Sigma with R. Statistical engineering for process improvement. (2012)
  14. Nolan, John P.: R as a tool in computational finance (2012)
  15. Wollschläger, Daniel: Foundations of data analysis with R. An application oriented introduction. (2010)