BayesX

R package BayesX: R Utilities Accompanying the Software Package BayesX. Functions for exploring and visualising estimation results obtained with BayesX, a free software for estimating structured additive regression models (<http://www.BayesX.org>). In addition, functions that allow to read, write and manipulate map objects that are required in spatial analyses performed with BayesX.

This software is also peer reviewed by journal JSS.


References in zbMATH (referenced in 94 articles , 3 standard articles )

Showing results 1 to 20 of 94.
Sorted by year (citations)

1 2 3 4 5 next

  1. Wiemann, Paul F. V.; Klein, Nadja; Kneib, Thomas: Correcting for sample selection bias in Bayesian distributional regression models (2022)
  2. Fasiolo, M., Wood, S. N., Zaffran, M., Nedellec, R., Goude, Y. : qgam: Bayesian Nonparametric Quantile Regression Modeling in R (2021) not zbMATH
  3. Klein, Nadja; Carlan, Manuel; Kneib, Thomas; Lang, Stefan; Wagner, Helga: Bayesian effect selection in structured additive distributional regression models (2021)
  4. Mayrink, V. D., Duarte, J. D. N., Demarqui, F. N.: pexm: A JAGS Module for Applications Involving the Piecewise Exponential Distribution (2021) not zbMATH
  5. Umlauf, N., Klein, N., Simon, T., Zeileis, A: bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond) (2021) not zbMATH
  6. Klein, Nadja; Herwartz, Helmut; Kneib, Thomas: Modelling regional patterns of inefficiency: a Bayesian approach to geoadditive panel stochastic frontier analysis with an application to cereal production in England and Wales (2020)
  7. Santos, Bruno; Kneib, Thomas: Noncrossing structured additive multiple-output Bayesian quantile regression models (2020)
  8. Wood, Simon N.: Inference and computation with generalized additive models and their extensions (2020)
  9. Amaral Turkman, Maria Antónia; Paulino, Carlos Daniel; Müller, Peter: Computational Bayesian statistics. An introduction (2019)
  10. Djeundje, Viani Biatat; Crook, Jonathan: Identifying hidden patterns in credit risk survival data using generalised additive models (2019)
  11. Klein, Nadja; Smith, Michael Stanley: Implicit copulas from Bayesian regularized regression smoothers (2019)
  12. 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)
  13. Liu, Li; Xiang, Liming: Missing covariate data in generalized linear mixed models with distribution-free random effects (2019)
  14. John Monaco; Malka Gorfine; Li Hsu: General Semiparametric Shared Frailty Model: Estimation and Simulation with frailtySurv (2018) not zbMATH
  15. Müeller, Peter; Quintana, Fernando A.; Page, Garritt: Nonparametric Bayesian inference in applications (2018)
  16. Tutz, Gerhard; Berger, Moritz: Tree-structured modelling of categorical predictors in generalized additive regression (2018)
  17. Waldmann, Elisabeth: Quantile regression: a short story on how and why (2018)
  18. Zhou, Haiming; Hanson, Timothy: A unified framework for Fitting Bayesian semiparametric models to arbitrarily censored survival data, including spatially referenced data (2018)
  19. Bai, Jiawei; Ivanescu, Andrada; Crainiceanu, Ciprian M.: Discussion of: “A general framework for functional regression modelling” (2017)
  20. Benjamin Taylor and Barry Rowlingson: spatsurv: An R Package for Bayesian Inference with Spatial Survival Models (2017) not zbMATH

1 2 3 4 5 next