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Numerical Methods for Bayesian Inference

BOOK CHAPTER published 2014 in Applied Statistical Inference

Authors: Leonhard Held | Daniel Sabanés Bové

Generalization of Dempster–Shafer theory: A complex mass function

JOURNAL ARTICLE published October 2020 in Applied Intelligence

Research funded by Fundamental Research Funds for the Central Universities (XDJK2019C085)

Authors: Fuyuan Xiao

Pseudo-Likelihoods for Bayesian Inference

BOOK CHAPTER published 2016 in Topics on Methodological and Applied Statistical Inference

Authors: Laura Ventura | Walter Racugno

Bayesian inference and the parametric bootstrap

JOURNAL ARTICLE published 1 December 2012 in The Annals of Applied Statistics

Authors: Bradley Efron

Inference in Bayesian additive vector autoregressive tree models

JOURNAL ARTICLE published 1 March 2022 in The Annals of Applied Statistics

Authors: Florian Huber | Luca Rossini

Bayesian inference for queueing networks and modeling of internet services

JOURNAL ARTICLE published 1 March 2011 in The Annals of Applied Statistics

Authors: Charles Sutton | Michael I. Jordan

Bayesian hierarchical modeling for signaling pathway inference from single cell interventional data

JOURNAL ARTICLE published 1 June 2011 in The Annals of Applied Statistics

Authors: Ruiyan Luo | Hongyu Zhao

Bayesian Inference for Generalized Additive Mixed Models Based on Markov Random Field Priors

JOURNAL ARTICLE published 1 June 2001 in Journal of the Royal Statistical Society Series C: Applied Statistics

Authors: Ludwig Fahrmeir | Stefan Lang

Bayesian optimal interval designs for phase I clinical trials

JOURNAL ARTICLE published April 2015 in Journal of the Royal Statistical Society: Series C (Applied Statistics)

Research funded by National Cancer Institute (CA154591)

Authors: Suyu Liu | Ying Yuan

Full Bayesian inference in hidden Markov models of plant growth

JOURNAL ARTICLE published 1 December 2022 in The Annals of Applied Statistics

Authors: Gautier Viaud | Yuting Chen | Paul-Henry Cournède

Bayesian Cox regression for large-scale inference with applications to electronic health records

JOURNAL ARTICLE published 1 June 2023 in The Annals of Applied Statistics

Authors: Alexander Wolfgang Jung | Moritz Gerstung

Bayesian inference for double Pareto lognormal queues

JOURNAL ARTICLE published 1 September 2010 in The Annals of Applied Statistics

Authors: Pepa Ramirez-Cobo | Rosa E. Lillo | Simon Wilson | Michael P. Wiper

Bayesian semiparametric inference for multivariate doubly-interval-censored data

JOURNAL ARTICLE published 1 December 2010 in The Annals of Applied Statistics

Authors: Alejandro Jara | Emmanuel Lesaffre | Maria De Iorio | Fernando Quintana

Bayesian Inference for Volatility of Stock Prices

JOURNAL ARTICLE published 1 November 2014 in Journal of Modern Applied Statistical Methods

Authors: Juliet G D'Cunha | K. A Rao

Bayesian inference and dynamic prediction for multivariate longitudinal and survival data

JOURNAL ARTICLE published 1 September 2023 in The Annals of Applied Statistics

Authors: Haotian Zou | Donglin Zeng | Luo Xiao | Sheng Luo

Bayesian Inference for Median of the Lognormal Distribution

JOURNAL ARTICLE published 1 November 2016 in Journal of Modern Applied Statistical Methods

Authors: K. Aruna Rao | Juliet Gratia D'Cunha

Approximate Bayesian inference for analysis of spatiotemporal flood frequency data

JOURNAL ARTICLE published 1 June 2022 in The Annals of Applied Statistics

Authors: Árni V. Jóhannesson | Stefan Siegert | Raphaël Huser | Haakon Bakka | Birgir Hrafnkelsson

Estimating limits from Poisson counting data using Dempster–Shafer analysis

JOURNAL ARTICLE published 1 June 2009 in The Annals of Applied Statistics

Authors: Paul T. Edlefsen | Chuanhai Liu | Arthur P. Dempster

Conflicts in Bayesian Statistics Between Inference Based on Credible Intervals and Bayes Factors

JOURNAL ARTICLE published 1 April 2020 in Journal of Modern Applied Statistical Methods

Authors: Miodrag M. Lovric

Bayesian Methods for Complex Data

BOOK CHAPTER published 19 May 2010 in Applied Bayesian Hierarchical Methods