-
1
-
-
0000294132
-
The choice of variables in multivariate regression: A non-conjugate Bayesian decision theory approach
-
BROWN, P. J., FEARN, T. and VANNUCCI, M. (1999). The choice of variables in multivariate regression: A non-conjugate Bayesian decision theory approach. Biometrika 86 635-648.
-
(1999)
Biometrika
, vol.86
, pp. 635-648
-
-
BROWN, P.J.1
FEARN, T.2
VANNUCCI, M.3
-
3
-
-
15944399178
-
Sparse graphical models for exploring gene expression data
-
DOBRA, A., HANS, C., JONES, B., NEVINS, J. R., YAO, G. and WEST, M. (2004). Sparse graphical models for exploring gene expression data. J. Multivariate Anal. 90 196-212.
-
(2004)
J. Multivariate Anal
, vol.90
, pp. 196-212
-
-
DOBRA, A.1
HANS, C.2
JONES, B.3
NEVINS, J.R.4
YAO, G.5
WEST, M.6
-
4
-
-
3142617128
-
Discussion on boosting
-
FRIEDMAN, J., HASTIE, T., ROSSET, S., TIBSHIRANI, R. and ZHU, J. (2004). Discussion on boosting. Ann. Statist. 32 102-107.
-
(2004)
Ann. Statist
, vol.32
, pp. 102-107
-
-
FRIEDMAN, J.1
HASTIE, T.2
ROSSET, S.3
TIBSHIRANI, R.4
ZHU, J.5
-
5
-
-
0021518209
-
Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
-
GEMAN, S. and GEMAN, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Machine Intell. 6 721-741.
-
(1984)
IEEE Trans. Pattern Anal. Machine Intell
, vol.6
, pp. 721-741
-
-
GEMAN, S.1
GEMAN, D.2
-
6
-
-
0031526204
-
Approaches for Bayesian variable selection
-
GEORGE, E. I. and MCCULLOCH, R. E. (1997). Approaches for Bayesian variable selection. Statist. Sinica 7 339-373.
-
(1997)
Statist. Sinica
, vol.7
, pp. 339-373
-
-
GEORGE, E.I.1
MCCULLOCH, R.E.2
-
7
-
-
0036000545
-
Bayesian variable selection in logistic regression: Predicting company earnings direction
-
GERLACH, R., BIRD, R. and HALL, A. (2002). Bayesian variable selection in logistic regression: Predicting company earnings direction. Aust. N. Z. J. Statist. 44 155-168.
-
(2002)
Aust. N. Z. J. Statist
, vol.44
, pp. 155-168
-
-
GERLACH, R.1
BIRD, R.2
HALL, A.3
-
9
-
-
0000444966
-
A smoothed maximum score estimator for the binary response model
-
HOROWITZ, J. L. (1992). A smoothed maximum score estimator for the binary response model. Econometrica 60 505-531.
-
(1992)
Econometrica
, vol.60
, pp. 505-531
-
-
HOROWITZ, J.L.1
-
10
-
-
33746227433
-
Misspecification in infinite-dimensional Bayesian statistics
-
KLEIJN, B. J. K. and VAN DER VAART, A. W. (2006). Misspecification in infinite-dimensional Bayesian statistics. Ann. Statist. 34 837-877.
-
(2006)
Ann. Statist
, vol.34
, pp. 837-877
-
-
KLEIJN, B.J.K.1
VAN DER VAART, A.W.2
-
11
-
-
50449090913
-
Bayesian variable selection for high dimensional generalized linear models: Convergence rates of the fitted densities
-
JIANG, W. (2007). Bayesian variable selection for high dimensional generalized linear models: Convergence rates of the fitted densities. Ann. Statist. 35 1487-1511.
-
(2007)
Ann. Statist
, vol.35
, pp. 1487-1511
-
-
JIANG, W.1
-
12
-
-
12244265090
-
Gene selection: A Bayesian variable selection approach
-
LEE, K. E., SHA, N., DOUGHERTY, E. R., VANNUCCI, M. and MALLICK, B. K. (2003). Gene selection: A Bayesian variable selection approach. Bioinformatics 19 90-97.
-
(2003)
Bioinformatics
, vol.19
, pp. 90-97
-
-
LEE, K.E.1
SHA, N.2
DOUGHERTY, E.R.3
VANNUCCI, M.4
MALLICK, B.K.5
-
13
-
-
0002438052
-
The choice of variables in multiple regression (with discussion)
-
LINDLEY, D. V. (1968). The choice of variables in multiple regression (with discussion). J. Roy. Statist. Assoc. Ser. B 30 31-66.
-
(1968)
J. Roy. Statist. Assoc. Ser. B
, vol.30
, pp. 31-66
-
-
LINDLEY, D.V.1
-
14
-
-
0000824232
-
Nonparametric regression using Bayesian variable selection
-
SMITH, M. and KOHN, R. (1996). Nonparametric regression using Bayesian variable selection. J. Econometrics 75 317-343.
-
(1996)
J. Econometrics
, vol.75
, pp. 317-343
-
-
SMITH, M.1
KOHN, R.2
-
16
-
-
84950758368
-
The calculation of posterior distributions by data augmentation (with discussion)
-
TANNER, M. A. and WONG, W. H. (1987). The calculation of posterior distributions by data augmentation (with discussion). J. Amer. Statist. Assoc. 82 528-550.
-
(1987)
J. Amer. Statist. Assoc
, vol.82
, pp. 528-550
-
-
TANNER, M.A.1
WONG, W.H.2
-
18
-
-
33847361463
-
From ε-entropy to KL-entropy: Analysis of minimum information complexity density estimation
-
ZHANG, T. (2006a). From ε-entropy to KL-entropy: Analysis of minimum information complexity density estimation. Ann. Statist. 34 2180-2210.
-
(2006)
Ann. Statist
, vol.34
, pp. 2180-2210
-
-
ZHANG, T.1
-
19
-
-
33645722194
-
Information theoretical upper and lower bounds for statistical estimation
-
ZHANG, T. (2006b). Information theoretical upper and lower bounds for statistical estimation. IEEE Trans. Inform. Theory 52 1307-1321.
-
(2006)
IEEE Trans. Inform. Theory
, vol.52
, pp. 1307-1321
-
-
ZHANG, T.1
-
20
-
-
4744364173
-
Cancer classification and prediction using logistic regression with Bayesian gene selection
-
ZHOU, X., LIU, K.-Y. and WONG, S. T. C. (2004). Cancer classification and prediction using logistic regression with Bayesian gene selection. J. Biomedical Informatics 37 249-259.
-
(2004)
J. Biomedical Informatics
, vol.37
, pp. 249-259
-
-
ZHOU, X.1
LIU, K.-Y.2
WONG, S.T.C.3
|