mgcv

R package mgcv: Mixed GAM Computation Vehicle with GCV/AIC/REML smoothness estimation. Routines for GAMs and other generalized ridge regression with multiple smoothing parameter selection by GCV, REML or UBRE/AIC. Also GAMMs. Includes a gam() function.

Keywords for this software

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References in zbMATH (referenced in 84 articles , 1 standard article )

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  1. Evandro Konzen, Yafeng Cheng, Jian Qing Shi: Gaussian Process for Functional Data Analysis: The GPFDA Package for R (2021) arXiv
  2. Ben Youngman: evgam: An R package for Generalized Additive Extreme Value Models (2020) arXiv
  3. Ferrara, Giancarlo: Stochastic frontier models using R (2020)
  4. Greven, Sonja; Scheipl, Fabian: Comments on: “Inference and computation with generalized additive models and their extensions” (2020)
  5. Hasler, Caren; Craiu, Radu V.: Nonparametric imputation method for nonresponse in surveys (2020)
  6. Miller, David L.; Glennie, Richard; Seaton, Andrew E.: Understanding the stochastic partial differential equation approach to smoothing (2020)
  7. Monterrubio-Gómez, Karla; Roininen, Lassi; Wade, Sara; Damoulas, Theodoros; Girolami, Mark: Posterior inference for sparse hierarchical non-stationary models (2020)
  8. Puth, Marie-Therese; Tutz, Gerhard; Heim, Nils; Münster, Eva; Schmid, Matthias; Berger, Moritz: Tree-based modeling of time-varying coefficients in discrete time-to-event models (2020)
  9. Torsten Hothorn: Most Likely Transformations: The mlt Package (2020) not zbMATH
  10. Xiao, Luo: Asymptotic properties of penalized splines for functional data (2020)
  11. Brizzi, Francesco; Birrell, Paul J.; Plummer, Martyn T.; Kirwan, Peter; Brown, Alison E.; Delpech, Valerie C.; Gill, O. Noel; De Angelis, Daniela: Extending Bayesian back-calculation to estimate age and time specific HIV incidence (2019)
  12. Djeundje, Viani Biatat; Crook, Jonathan: Dynamic survival models with varying coefficients for credit risks. (2019)
  13. Djeundje, Viani Biatat; Crook, Jonathan: Identifying hidden patterns in credit risk survival data using generalised additive models (2019)
  14. Haziq Jamil, Wicher Bergsma: iprior: An R Package for Regression Modelling using I-priors (2019) arXiv
  15. Kneib, Thomas; Klein, Nadja; Lang, Stefan; Umlauf, Nikolaus: Modular regression -- a Lego system for building structured additive distributional regression models with tensor product interactions (2019)
  16. Reimherr, Matthew: Comments on “Modular regression -- a Lego system for building structured additive distributional regression models with tensor product interactions” (2019)
  17. Seongil Jo; Taeryon Choi; Beomjo Park; Peter Lenk: bsamGP: An R Package for Bayesian Spectral Analysis Models Using Gaussian Process Priors (2019) not zbMATH
  18. Victor Maus and Gilberto Câmara and Marius Appel and Edzer Pebesma: dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R (2019) not zbMATH
  19. Zeldow, Bret; Lo Re, Vincent III; Roy, Jason: A semiparametric modeling approach using Bayesian additive regression trees with an application to evaluate heterogeneous treatment effects (2019)
  20. Zhang, Youyi; Morris, Jeffrey S.; Aerry, Shivali Narang; Rao, Arvind U. K.; Baladandayuthapani, Veerabhadran: Radio-iBAG: radiomics-based integrative Bayesian analysis of multiplatform genomic data (2019)

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