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Andrew Gelman
Andrew Gelman
Professor of Statistics and Political Science, Columbia University
Verified email at stat.columbia.edu - Homepage
Title
Cited by
Cited by
Year
Bayesian data analysis, 3rd edition
A Gelman, JB Carlin, HS Stern, DB Dunson, A Vehtari, DB Rubin
Chapman & Hall/CRC, 2013
39393*2013
Inference from iterative simulation using multiple sequences
A Gelman, DB Rubin
Statistical science 7 (4), 457-472, 1992
191881992
Data analysis using regression and multilevel/hierarchical models
A Gelman
Cambridge university press, 2007
190662007
Stan: A probabilistic programming language
B Carpenter, A Gelman, MD Hoffman, D Lee, B Goodrich, M Betancourt, ...
Journal of statistical software 76, 2017
80642017
General methods for monitoring convergence of iterative simulations
SP Brooks, A Gelman
Journal of computational and graphical statistics 7 (4), 434-455, 1998
80191998
The No-U-Turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo.
MD Hoffman, A Gelman
J. Mach. Learn. Res. 15 (1), 1593-1623, 2014
56292014
Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)
A Gelman
55822006
Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
A Vehtari, A Gelman, J Gabry
Statistics and computing 27, 1413-1432, 2017
50192017
Handbook of markov chain monte carlo
S Brooks, A Gelman, G Jones, XL Meng
CRC press, 2011
34952011
Posterior predictive assessment of model fitness via realized discrepancies
A Gelman, XL Meng, H Stern
Statistica sinica, 733-760, 1996
30561996
Scaling regression inputs by dividing by two standard deviations
A Gelman
Statistics in medicine 27 (15), 2865-2873, 2008
26302008
Weak convergence and optimal scaling of random walk Metropolis algorithms
A Gelman, WR Gilks, GO Roberts
The annals of applied probability 7 (1), 110-120, 1997
24231997
A weakly informative default prior distribution for logistic and other regression models
A Gelman, A Jakulin, MG Pittau, YS Su
23542008
Understanding predictive information criteria for Bayesian models
A Gelman, J Hwang, A Vehtari
Statistics and computing 24, 997-1016, 2014
23182014
Why high-order polynomials should not be used in regression discontinuity designs
A Gelman, G Imbens
Journal of Business & Economic Statistics 37 (3), 447-456, 2019
21312019
R2WinBUGS: a package for running WinBUGS from R
S Sturtz, U Ligges, A Gelman
Journal of Statistical software 12, 1-16, 2005
20712005
Efficient Metropolis jumping rules
A Gelman, GO Roberts, WR Gilks
Bayesian statistics 5 (599-608), 42, 1996
16021996
Why we (usually) don't have to worry about multiple comparisons
A Gelman, J Hill, M Yajima
Journal of research on educational effectiveness 5 (2), 189-211, 2012
15162012
Beyond power calculations: Assessing type S (sign) and type M (magnitude) errors
A Gelman, J Carlin
Perspectives on psychological science 9 (6), 641-651, 2014
14192014
Rank-normalization, folding, and localization: An improved R ̂ for assessing convergence of MCMC (with discussion)
A Vehtari, A Gelman, D Simpson, B Carpenter, PC Bürkner
Bayesian analysis 16 (2), 667-718, 2021
13672021
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