References in zbMATH (referenced in 14 articles )

Showing results 1 to 14 of 14.
Sorted by year (citations)

  1. David Smith; Malcolm Faddy: Mean and Variance Modeling of Under-Dispersed and Over-Dispersed Grouped Binary Data (2019) not zbMATH
  2. Di Caterina, Claudia; Kosmidis, Ioannis: Location-adjusted Wald statistics for scalar parameters (2019)
  3. Hay-Jahans, Christopher: R companion to elementary applied statistics (2019)
  4. Tarak Kharrat; Georgi Boshnakov; Ian McHale; Rose Baker: Flexible Regression Models for Count Data Based on Renewal Processes: The Countr Package (2019) not zbMATH
  5. Stübinger, Johannes; Endres, Sylvia: Pairs trading with a mean-reverting jump-diffusion model on high-frequency data (2018)
  6. Valliant, Richard; Dever, Jill A.; Kreuter, Frauke: Practical tools for designing and weighting survey samples (2018)
  7. Howard, James P. II: Computational methods for numerical analysis with R (2017)
  8. Gerhart, Christoph: A multiple-curve Lévy forward rate model in a two-price economy (2016)
  9. Antony Overstall; Ruth King: conting: An R Package for Bayesian Analysis of Complete and Incomplete Contingency Tables (2014) not zbMATH
  10. Bonnini, Stefano; Corain, Livio; Marozzi, Marco; Salmaso, Luigi: Nonparametric hypothesis testing. Rank and permutation methods with applications in R (2014)
  11. Nash, John C.: Nonlinear parameter optimization using R tools (2014)
  12. van Hees VT, Fang Z, Langford J, Assah F, Mohammad A, da Silva IC, Trenell MI, White T, Wareham NJ, Brage S.: Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents (2014) not zbMATH
  13. Valliant, Richard; Dever, Jill A.; Kreuter, Frauke: Practical tools for designing and weighting survey samples (2013)
  14. Kaas, Rob; Goovaerts, Marc; Dhaene, Jan; Denuit, Michel: Modern actuarial risk theory. Using R (2008)