GAMLSS

R package gamlss: Generalised Additive Models for Location Scale and Shape. The library for fitting GAMLSS models.

Keywords for this software

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References in zbMATH (referenced in 166 articles , 1 standard article )

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  1. Ben Youngman: evgam: An R package for Generalized Additive Extreme Value Models (2020) arXiv
  2. Brouste, Alexandre; Dutang, Christophe; Rohmer, Tom: Closed-form maximum likelihood estimator for generalized linear models in the case of categorical explanatory variables: application to insurance loss modeling (2020)
  3. Fan, Jianqing; Feng, Yang; Xia, Lucy: A projection-based conditional dependence measure with applications to high-dimensional undirected graphical models (2020)
  4. Ferrara, Giancarlo: Stochastic frontier models using R (2020)
  5. Gonçalves, Jussiane Nader; Barreto-Souza, Wagner: Flexible regression models for counts with high-inflation of zeros (2020)
  6. Hothorn, Torsten: Transformation boosting machines (2020)
  7. Huang, Yifan; Meng, Shengwang: A Bayesian nonparametric model and its application in insurance loss prediction (2020)
  8. Razen, Alexander; Lang, Stefan: Random scaling factors in Bayesian distributional regression models with an application to real estate data (2020)
  9. Scudilio, Juliana; Pereira, Gustavo H. A.: Adjusted quantile residual for generalized linear models (2020)
  10. Spiegel, Elmar; Kneib, Thomas; Otto-Sobotka, Fabian: Spatio-temporal expectile regression models (2020)
  11. Tzougas, George; Karlis, Dimitris: An EM algorithm for fitting a new class of mixed exponential regression models with varying dispersion (2020)
  12. van der Wurp, Hendrik; Groll, Andreas; Kneib, Thomas; Marra, Giampiero; Radice, Rosalba: Generalised joint regression for count data: a penalty extension for competitive settings (2020)
  13. Wood, Simon N.: Inference and computation with generalized additive models and their extensions (2020)
  14. Canterle, Diego Ramos; Bayer, Fábio Mariano: Variable dispersion beta regressions with parametric link functions (2019)
  15. Chen, Yen-Chi; Choe, Youngjun: Importance sampling and its optimality for stochastic simulation models (2019)
  16. El-Bachir, Yousra; Davison, Anthony C.: Fast automatic smoothing for generalized additive models (2019)
  17. Fang, Kuangnan; Fan, Xinyan; Lan, Wei; Wang, Bingquan: Nonparametric additive beta regression for fractional response with application to body fat data (2019)
  18. Filippou, Panagiota; Kneib, Thomas; Marra, Giampiero; Radice, Rosalba: A trivariate additive regression model with arbitrary link functions and varying correlation matrix (2019)
  19. Groll, Andreas; Hambuckers, Julien; Kneib, Thomas; Umlauf, Nikolaus: LASSO-type penalization in the framework of generalized additive models for location, scale and shape (2019)
  20. Hui, Francis K. C.; You, C.; Shang, H. L.; Müller, Samuel: Semiparametric regression using variational approximations (2019)

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