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The Gibbs sampler, the algorithm of Metropolis, and similar iterative simulation methods are potentially very helpful for summarizing multivariate distributions. Used naively, however, iterativeâ€¦ (More)

- Robert E. Kass, Panelists, Bradley P. Carlin, Andrew Gelman, Mark Radford
- 1997

Markov chain Monte Carlo (MCMC) methods make possible the use of flexible Bayesian models that would otherwise be computationally infeasible. In recent years, a great variety of such applicationsâ€¦ (More)

- Andrew Gelman
- 2004

Various noninformative prior distributions have been suggested for scale parameters in hierarchical models. We construct a new folded-noncentral-t family of conditionally conjugate priors forâ€¦ (More)

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology andâ€¦ (More)

- Matthew D. Hoffman, Andrew Gelman
- Journal of Machine Learning Research
- 2014

Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo (MCMC) algorithm that avoids the random walk behavior and sensitivity to correlated parameters that plague many MCMC methods by taking aâ€¦ (More)

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology andâ€¦ (More)

- Andrew Gelman, John B Carlin, +6 authors Corey Yanovsky
- 2009

4 Mar 2012 These solutions are in progress. For more information on either the solutions or the book (published by CRC), check the website, http://www.stat.columbia.edu/âˆ¼gelman/book/ For each graphâ€¦ (More)

- Andrew Gelman
- 1997

Computing (ratios of) normalizing constants of probability models is a fundamental computational problem for many statistical and scientific studies. Monte Carlo simulation is an effective technique,â€¦ (More)

We propose a new prior distribution for classical (non-hierarchical) logistic regression models, constructed by first scaling all nonbinary variables to have mean 0 and standard deviation 0.5, andâ€¦ (More)

- Andrew Gelman
- Statistics in medicine
- 2008

Interpretation of regression coefficients is sensitive to the scale of the inputs. One method often used to place input variables on a common scale is to divide each numeric variable by its standardâ€¦ (More)