References in zbMATH (referenced in 77 articles )

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  1. Pal, Suvra; Majakwara, Jacob; Balakrishnan, N.: An EM algorithm for the destructive COM-Poisson regression cure rate model (2018)
  2. Thomas, Janek; Mayr, Andreas; Bischl, Bernd; Schmid, Matthias; Smith, Adam; Hofner, Benjamin: Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates (2018)
  3. Burke, K.; MacKenzie, G.: Multi-parameter regression survival modeling: an alternative to proportional hazards (2017)
  4. Langrock, Roland; Kneib, Thomas; Glennie, Richard; Michelot, Théo: Markov-switching generalized additive models (2017)
  5. Mamouridis, Valeria; Klein, Nadja; Kneib, Thomas; Cadarso Suarez, Carmen; Maynou, Francesc: Structured additive distributional regression for analysing landings per unit effort in fisheries research (2017)
  6. Marra, Giampiero; Radice, Rosalba: A joint regression modeling framework for analyzing bivariate binary data in $\mathsfR$ (2017)
  7. Starunova, Olga A.; Rudnev, Sergey G.; Starodubov, Vladimir I.: HCViewer: software and technology for quality control and processing raw mass data of preventive screening (2017)
  8. Vanegas, Luis Hernando; Paula, Gilberto A.: Log-symmetric regression models under the presence of non-informative left- or right-censored observations (2017)
  9. Wood, Simon N.: Generalized additive models. An introduction with R. (2017)
  10. Antoniadis, Anestis; Gijbels, Irène; Lambert-Lacroix, Sophie; Poggi, Jean-Michel: Joint estimation and variable selection for mean and dispersion in proper dispersion models (2016)
  11. Barreto-Souza, Wagner; Simas, Alexandre B.: General mixed Poisson regression models with varying dispersion (2016)
  12. Heinzl, Felix; Tutz, Gerhard: Additive mixed models with approximate Dirichlet process mixtures: the EM approach (2016)
  13. Hofner, Benjamin; Kneib, Thomas; Hothorn, Torsten: A unified framework of constrained regression (2016)
  14. Klein, Nadja; Kneib, Thomas: Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach (2016)
  15. Maruotti, Antonello; Raponi, Valentina; Lagona, Francesco: Handling endogeneity and nonnegativity in correlated random effects models: evidence from ambulatory expenditure (2016)
  16. Relvas, Carlos Eduardo M.; Paula, Gilberto A.: Partially linear models with first-order autoregressive symmetric errors (2016)
  17. Scheipl, Fabian; Gertheiss, Jan; Greven, Sonja: Generalized functional additive mixed models (2016)
  18. Tong, Edward N.C.; Mues, Christophe; Brown, Iain; Thomas, Lyn C.: Exposure at default models with and without the credit conversion factor (2016)
  19. Wang, Jue; Luo, Sheng: Augmented beta rectangular regression models: A Bayesian perspective (2016)
  20. Wanke, Peter; Ewbank, Henrique; Leiva, Víctor; Rojas, Fernando: Inventory management for new products with triangularly distributed demand and lead-time (2016)

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