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 69 articles , 3 standard articles )

Showing results 1 to 20 of 69.
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  1. Amaral Turkman, Maria Antónia; Paulino, Carlos Daniel; Müller, Peter: Computational Bayesian statistics. An introduction (2019)
  2. Djeundje, Viani Biatat; Crook, Jonathan: Identifying hidden patterns in credit risk survival data using generalised additive models (2019)
  3. Liu, Li; Xiang, Liming: Missing covariate data in generalized linear mixed models with distribution-free random effects (2019)
  4. John Monaco; Malka Gorfine; Li Hsu: General Semiparametric Shared Frailty Model: Estimation and Simulation with frailtySurv (2018) not zbMATH
  5. Müeller, Peter; Quintana, Fernando A.; Page, Garritt: Nonparametric Bayesian inference in applications (2018)
  6. Tutz, Gerhard; Berger, Moritz: Tree-structured modelling of categorical predictors in generalized additive regression (2018)
  7. Zhou, Haiming; Hanson, Timothy: A unified framework for Fitting Bayesian semiparametric models to arbitrarily censored survival data, including spatially referenced data (2018)
  8. Benjamin Taylor and Barry Rowlingson: spatsurv: An R Package for Bayesian Inference with Spatial Survival Models (2017) not zbMATH
  9. Groll, Andreas; Tutz, Gerhard: Variable selection in discrete survival models including heterogeneity (2017)
  10. Haiming Zhou, Timothy Hanson, Jiajia Zhang: spBayesSurv: Fitting Bayesian Spatial Survival Models Using R (2017) arXiv
  11. John V. Monaco, Malka Gorfine, Li Hsu: General Semiparametric Shared Frailty Model Estimation and Simulation with frailtySurv (2017) arXiv
  12. Oelker, Margret-Ruth; Tutz, Gerhard: A uniform framework for the combination of penalties in generalized structured models (2017)
  13. Schmidt, Paul; Mühlau, Mark; Schmid, Volker: Fitting large-scale structured additive regression models using Krylov subspace methods (2017)
  14. Heinzl, Felix; Tutz, Gerhard: Additive mixed models with approximate Dirichlet process mixtures: the EM approach (2016)
  15. Klein, Nadja; Kneib, Thomas: Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach (2016)
  16. Simon Wood: Just Another Gibbs Additive Modeler: Interfacing JAGS and mgcv (2016) not zbMATH
  17. Choi, Taeryon; Woo, Yoonsung: A partially linear model using a Gaussian process prior (2015)
  18. Edzer Pebesma; Roger Bivand; Paulo Ribeiro: Software for Spatial Statistics (2015) not zbMATH
  19. Eilers, Paul H. C.; Marx, Brian D.; Durbán, Maria: Twenty years of P-splines (invited article) (2015)
  20. Klein, Nadja; Kneib, Thomas; Lang, Stefan; Sohn, Alexander: Bayesian structured additive distributional regression with an application to regional income inequality in Germany (2015)

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