Robert E. Kass
Robert E. Kass
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Cited by
Cited by
Bayes Factors
RE Kass, AE Raftery
Bayes Factors. J. Amer. Stat. Assoc 90 (430), 774-795, 1995
The selection of prior distributions by formal rules
RE Kass, L Wasserman
Journal of the American statistical Association 91 (435), 1343-1370, 1996
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
Multiple neural spike train data analysis: state-of-the-art and future challenges
EN Brown, RE Kass, PP Mitra
Nature neuroscience 7 (5), 456-461, 2004
Markov chain Monte Carlo in practice: a roundtable discussion
RE Kass, BP Carlin, A Gelman, RM Neal
The American Statistician 52 (2), 93-100, 1998
The time-rescaling theorem and its application to neural spike train data analysis
EN Brown, R Barbieri, V Ventura, RE Kass, LM Frank
Neural computation 14 (2), 325-346, 2002
Approximate Bayesian inference in conditionally independent hierarchical models (parametric empirical Bayes models)
RE Kass, D Steffey
Journal of the American Statistical Association 84 (407), 717-726, 1989
Bayesian curve‐fitting with free‐knot splines
I DiMatteo, CR Genovese, RE Kass
Biometrika 88 (4), 1055-1071, 2001
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
Fully exponential Laplace approximations to expectations and variances of nonpositive functions
L Tierney, RE Kass, JB Kadane
Journal of the American Statistical Association 84 (407), 710-716, 1989
Geometrical foundations of asymptotic inference
RE Kass, PW Vos
John Wiley & Sons, 2011
Differential Geometry in Statistical Inference
SI Amari, OE Barndorff-Nielsen, RE Kass, SL Lauritzen, CR Rao
Differential Geometry in Statistical Inference, 1987
Statistical issues in the analysis of neuronal data
RE Kass, V Ventura, EN Brown
Journal of neurophysiology 94 (1), 8-25, 2005
Automatic correction of ocular artifacts in the EEG: a comparison of regression-based and component-based methods
GL Wallstrom, RE Kass, A Miller, JF Cohn, NA Fox
International journal of psychophysiology 53 (2), 105-119, 2004
Shrinkage estimators for covariance matrices
MJ Daniels, RE Kass
Biometrics 57 (4), 1173-1184, 2001
Functional network reorganization during learning in a brain-computer interface paradigm
B Jarosiewicz, SM Chase, GW Fraser, M Velliste, RE Kass, AB Schwartz
Proceedings of the National Academy of Sciences 105 (49), 19486-19491, 2008
The geometry of asymptotic inference
RE Kass
Statistical Science, 188-219, 1989
The validity of posterior expansions based on Laplace’s method
S Geisser, J Hodges, S Press, A ZeUner
Bayesian and likelihood methods in statistics and econometrics 7, 473, 1990
Recursive Bayesian decoding of motor cortical signals by particle filtering
AE Brockwell, AL Rojas, RE Kass
Journal of neurophysiology 91 (4), 1899-1907, 2004
A spike-train probability model
RE Kass, V Ventura
Neural computation 13 (8), 1713-1720, 2001
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