Larry Wasserman
Larry Wasserman
Professor, Department of Statistics and Machine Learning Department, Carnegie Mellon University
Dirección de correo verificada de stat.cmu.edu
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All of statistics: a concise course in statistical inference
L Wasserman
Springer Science & Business Media, 2013
4258*2013
All of statistics: a concise course in statistical inference
L Wasserman
Springer Science & Business Media, 2013
4258*2013
The selection of prior distributions by formal rules
RE Kass, L Wasserman
Journal of the American statistical Association 91 (435), 1343-1370, 1996
13841996
A reference Bayesian test for nested hypotheses and its relationship to the Schwarz criterion
RE Kass, L Wasserman
Journal of the american statistical association 90 (431), 928-934, 1995
13411995
Bayesian model selection and model averaging
L Wasserman
Journal of mathematical psychology 44 (1), 92-107, 2000
9082000
An overview of robust Bayesian analysis
JO Berger, E Moreno, LR Pericchi, MJ Bayarri, JM Bernardo, JA Cano, ...
Test 3 (1), 5-124, 1994
6401994
Operating characteristics and extensions of the false discovery rate procedure
C Genovese, L Wasserman
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2002
6282002
Practical Bayesian density estimation using mixtures of normals
K Roeder, L Wasserman
Journal of the American Statistical Association 92 (439), 894-902, 1997
6211997
Sparse additive models
P Ravikumar, J Lafferty, H Liu, L Wasserman
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2009
6012009
Computing Bayes factors using a generalization of the Savage-Dickey density ratio
I Verdinelli, L Wasserman
Journal of the American Statistical Association 90 (430), 614-618, 1995
5871995
Genomic control, a new approach to genetic-based association studies
B Devlin, K Roeder, L Wasserman
Theoretical population biology 60 (3), 155-166, 2001
5652001
The nonparanormal: Semiparametric estimation of high dimensional undirected graphs.
H Liu, J Lafferty, L Wasserman
Journal of Machine Learning Research 10 (10), 2009
5482009
High dimensional variable selection
L Wasserman, K Roeder
Annals of statistics 37 (5A), 2178, 2009
5172009
A stochastic process approach to false discovery control
C Genovese, L Wasserman
The Annals of Statistics 32 (3), 1035-1061, 2004
4282004
The consistency of posterior distributions in nonparametric problems
A Barron, MJ Schervish, L Wasserman
The Annals of Statistics 27 (2), 536-561, 1999
4271999
High-dimensional semiparametric Gaussian copula graphical models
H Liu, F Han, M Yuan, J Lafferty, L Wasserman
The Annals of Statistics 40 (4), 2293-2326, 2012
4242012
Computing Bayes factors by combining simulation and asymptotic approximations
TJ DiCiccio, RE Kass, A Raftery, L Wasserman
Journal of the American Statistical Association 92 (439), 903-915, 1997
4231997
A stochastic process approach to false discovery control
C Genovese, L Wasserman
The Annals of Statistics 32 (3), 1035-1061, 2004
4212004
Stability approach to regularization selection (stars) for high dimensional graphical models
H Liu, K Roeder, L Wasserman
Advances in neural information processing systems, 1432-1440, 2010
3592010
The huge package for high-dimensional undirected graph estimation in R
T Zhao, H Liu, K Roeder, J Lafferty, L Wasserman
The Journal of Machine Learning Research 13 (1), 1059-1062, 2012
3152012
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