crs

R package crs: Categorical Regression Splines. Regression splines that handle a mix of continuous and categorical (discrete) data often encountered in applied settings. I would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC:www.nserc.ca), the Social Sciences and Humanities Research Council of Canada (SSHRC:www.sshrc.ca), and the Shared Hierarchical Academic Research Computing Network (SHARCNET:www.sharcnet.ca).

Keywords for this software

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References in zbMATH (referenced in 6 articles )

Showing results 1 to 6 of 6.
Sorted by year (citations)

  1. Chu, Ba M.; Jacho-Chávez, David T.; Linton, Oliver B.: Standard errors for nonparametric regression (2020)
  2. Gadioli, Davide; Vitali, Emanuele; Palermo, Gianluca; Silvano, Cristina: mARGOt: a dynamic autotuning framework for self-aware approximate computing (2019)
  3. Lien, Donald; Hu, Yue; Liu, Long: A note on using ratio variables in regression analysis (2017)
  4. Gramacy, Robert B.; Bingham, Derek; Holloway, James Paul; Grosskopf, Michael J.; Kuranz, Carolyn C.; Rutter, Erica; Trantham, Matt; Drake, R. Paul: Calibrating a large computer experiment simulating radiative shock hydrodynamics (2015)
  5. Hall, Peter G.; Racine, Jeffrey S.: Infinite order cross-validated local polynomial regression (2015)
  6. Ma, Shujie; Racine, Jeffrey S.: Additive regression splines with irrelevant categorical and continuous regressors (2013)