Bayesian Data Analysis, 2nd edn
By A. Brix. 2005
2,488 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/48d287c7d01ee987f19e4738ba148bb8a4b297ee
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Jasper A. Vrugt
- Aki Vehtari
- Andrew Gelman
- Blakeley B. McShane
- Mattan S. Ben-Shachar
- Daniel Lüdecke
- Dominique Makowski
- Indrajeet Patil
In Statistics and Probability
- Jasper A. Vrugt
- Andrew Gelman
- Aki Vehtari
- Youssef M. Marzouk
- C. T. ter Braak
- Mattan S. Ben-Shachar
- Daniel Lüdecke
- Dominique Makowski
Citations in the corpus
- Assessing the integrated effects of landscape fragmentation on plants and plant communities: the challenge of multiprocess–multiresponse dynamics (2014, methodology): “We obtained those estimates through their prior distributions, letting the data from other groups and the relationships between groups inform them (Gelman et al. 2000).”
- An Efficient Stochastic Bayesian Approach to Optimal Parameter and Uncertainty Estimation for Climate Model Predictions (2004, background): “The effectiveness of any given sampling strategy depends on the appropriateness of the size of the steps used in sampling parameter space (Gelman et al. 2003).”
- Differential Evolution Markov Chain with snooker updater and fewer chains (2008, methodology): “Gelman et al. (2004) consider ˆ R below 1.2 acceptable.”
- Bayesian Hierarchical Models With Conjugate Full-Conditional Distributions for Dependent Data From the Natural Exponential Family (2017, neutral): “The Wishart and inverse Wishart are also common alternatives (e.g., see Gelman et al., 2013, for a standard reference).”