-
1
-
-
50849104032
-
-
AKAIKE, H. (1973). Information theory and an extension of the maximum likelihood principle. In Proc. 2nd Int. Symp. Information Theory (B. N. Petrov and F. Csáki, eds.) 267-281. Akadémiai Kiadó, Budapest. MR0483125
-
AKAIKE, H. (1973). Information theory and an extension of the maximum likelihood principle. In Proc. 2nd Int. Symp. Information Theory (B. N. Petrov and F. Csáki, eds.) 267-281. Akadémiai Kiadó, Budapest. MR0483125
-
-
-
-
2
-
-
0016029778
-
The relationship between variable selection and data augmentation and a method for prediction
-
MR0343481
-
ALLEN, D. M. (1974). The relationship between variable selection and data augmentation and a method for prediction. Technometrics 16 125-127. MR0343481
-
(1974)
Technometrics
, vol.16
, pp. 125-127
-
-
ALLEN, D.M.1
-
3
-
-
50849104866
-
-
BREIMAN, L., FRIEDMAN, J. H., OLSHEN, R. A. and STONE, C. J. (1984). Classification and Regression Trees. Wadsworth, Belmont, CA. MR0726392
-
BREIMAN, L., FRIEDMAN, J. H., OLSHEN, R. A. and STONE, C. J. (1984). Classification and Regression Trees. Wadsworth, Belmont, CA. MR0726392
-
-
-
-
4
-
-
0000354976
-
A comparative study of ordinary cross-validation, u-fold cross-validation and the repeated learning-testing methods
-
MR1040644
-
BURMAN, P. (1989). A comparative study of ordinary cross-validation, u-fold cross-validation and the repeated learning-testing methods. Biometrika 76 503-514. MR1040644
-
(1989)
Biometrika
, vol.76
, pp. 503-514
-
-
BURMAN, P.1
-
5
-
-
0009935784
-
Estimation of optimal transformations using u-fold cross validation and repeated learning-testing methods
-
MR1178041
-
BURMAN, P. (1990). Estimation of optimal transformations using u-fold cross validation and repeated learning-testing methods. Sankhyā Ser A 52 314-345. MR1178041
-
(1990)
Sankhyā Ser A
, vol.52
, pp. 314-345
-
-
BURMAN, P.1
-
6
-
-
34250263445
-
Smoothing noisy data with spline functions
-
MR0516581
-
CRAVEN, P. and WAHBA, G. (1979). Smoothing noisy data with spline functions. Numer. Math. 31 377-403. MR0516581
-
(1979)
Numer. Math
, vol.31
, pp. 377-403
-
-
CRAVEN, P.1
WAHBA, G.2
-
7
-
-
0032334093
-
Minimax estimation via wavelet shrinkage
-
MR 1635414
-
DONOHO, D. L. and JOHNSTONE, I. M. (1998). Minimax estimation via wavelet shrinkage. Ann. Statist. 26 879-921. MR 1635414
-
(1998)
Ann. Statist
, vol.26
, pp. 879-921
-
-
DONOHO, D.L.1
JOHNSTONE, I.M.2
-
8
-
-
50849106485
-
-
FAN, J. and GIJBELS, I. (1996). Local Polynomial Modelling and Its Applications. Chapman and Hall, London. MR1383587
-
FAN, J. and GIJBELS, I. (1996). Local Polynomial Modelling and Its Applications. Chapman and Hall, London. MR1383587
-
-
-
-
9
-
-
84950645271
-
The predictive sample reuse method with applications
-
GEISSER, S. (1975). The predictive sample reuse method with applications. J. Amer. Statist. Assoc. 70 320-328.
-
(1975)
J. Amer. Statist. Assoc
, vol.70
, pp. 320-328
-
-
GEISSER, S.1
-
10
-
-
0003624357
-
-
Springer, New York. MR 1920390
-
GYÖRFI, L., KOHLER, M., KRZYZAK, A. and WALK, H. (2002). A Distribution-Free Theory of Nonparametric Regression. Springer, New York. MR 1920390
-
(2002)
A Distribution-Free Theory of Nonparametric Regression
-
-
GYÖRFI, L.1
KOHLER, M.2
KRZYZAK, A.3
WALK, H.4
-
11
-
-
0000606681
-
Empirical functional and efficient smoothing parameter selection (with discussion)
-
MR 1160479
-
HALL, P. and JOHNSTONE, I. (1992). Empirical functional and efficient smoothing parameter selection (with discussion). J. Roy. Statist. Soc. Ser. B 54 475-530. MR 1160479
-
(1992)
J. Roy. Statist. Soc. Ser. B
, vol.54
, pp. 475-530
-
-
HALL, P.1
JOHNSTONE, I.2
-
12
-
-
84909719647
-
How far are automatically chosen regression smoothing parameters from their optimum? (with discussion)
-
MR0941001
-
HARDLE, W., HALL, P. and MARRON, J. S. (1988). How far are automatically chosen regression smoothing parameters from their optimum? (with discussion). J. Amer. Statist. Assoc. 83 86-101. MR0941001
-
(1988)
J. Amer. Statist. Assoc
, vol.83
, pp. 86-101
-
-
HARDLE, W.1
HALL, P.2
MARRON, J.S.3
-
14
-
-
0142064173
-
Consistency for cross-validated nearest neighbor estimates in nonparametric regression
-
MR0733510
-
LI, K.-C. (1984). Consistency for cross-validated nearest neighbor estimates in nonparametric regression. Ann. Statist. 12 230-240. MR0733510
-
(1984)
Ann. Statist
, vol.12
, pp. 230-240
-
-
LI, K.-C.1
-
15
-
-
0001462696
-
L, cross-validation and generalized crossvalidation: Discrete index set
-
MR0902239
-
L, cross-validation and generalized crossvalidation: Discrete index set. Ann. Statist. 15 958-975. MR0902239
-
(1987)
Ann. Statist
, vol.15
, pp. 958-975
-
-
LI, K.-C.1
-
16
-
-
0007259908
-
Topics in nonparametric statistics
-
Lectures on Probability Theory and Statistics Saint-Flour, Springer, Berlin. MR 1775640
-
NEMIROVSKI, A. (2000). Topics in nonparametric statistics. Lectures on Probability Theory and Statistics (Saint-Flour, 1998). Lecture Notes in Math. 1738 85-277. Springer, Berlin. MR 1775640
-
(1998)
Lecture Notes in Math
, vol.1738
, pp. 85-277
-
-
NEMIROVSKI, A.1
-
17
-
-
0009955854
-
Nonparametric regression with correlated errors
-
MR1861070
-
OPSOMER, J., WANG, Y. and YANG, Y. (2001). Nonparametric regression with correlated errors. Statist. Sci. 16 134-153. MR1861070
-
(2001)
Statist. Sci
, vol.16
, pp. 134-153
-
-
OPSOMER, J.1
WANG, Y.2
YANG, Y.3
-
18
-
-
50849143239
-
-
POLLARD, D. (1984). Convergence of Stochastic Processes. Springer, New York. MR0762984
-
POLLARD, D. (1984). Convergence of Stochastic Processes. Springer, New York. MR0762984
-
-
-
-
19
-
-
21144474350
-
Linear model selection by cross-validation
-
MR1224373
-
SHAO, J. (1993). Linear model selection by cross-validation. J. Amer. Statist. Assoc. 88 486-494. MR1224373
-
(1993)
J. Amer. Statist. Assoc
, vol.88
, pp. 486-494
-
-
SHAO, J.1
-
20
-
-
0642336882
-
An asymptotic theory for linear model selection (with discussion)
-
MR1466682
-
SHAO, J. (1997). An asymptotic theory for linear model selection (with discussion). Statist. Sinica 7 221-264. MR1466682
-
(1997)
Statist. Sinica
, vol.7
, pp. 221-264
-
-
SHAO, J.1
-
21
-
-
50849130652
-
-
SIMONOFF, J. S. (1996). Smoothing Methods in Statistics. Springer, New York. MR1391963
-
SIMONOFF, J. S. (1996). Smoothing Methods in Statistics. Springer, New York. MR1391963
-
-
-
-
22
-
-
0000935894
-
Spline smoothing and optimal rates of convergence in nonparametric regression models
-
MR0803752
-
SPECKMAN, P. (1985). Spline smoothing and optimal rates of convergence in nonparametric regression models. Ann. Statist. 13 970-983. MR0803752
-
(1985)
Ann. Statist
, vol.13
, pp. 970-983
-
-
SPECKMAN, P.1
-
23
-
-
0000439527
-
Optimal rates of convergence for nonparametric estimators
-
MR0594650
-
STONE, C. J. (1980). Optimal rates of convergence for nonparametric estimators. Ann. Statist. 8 1348-1360. MR0594650
-
(1980)
Ann. Statist
, vol.8
, pp. 1348-1360
-
-
STONE, C.J.1
-
24
-
-
0000439527
-
Optimal global rates of convergence for nonparametric regression
-
MR0673642
-
STONE, C. J. (1982). Optimal global rates of convergence for nonparametric regression. Ann. Statist. 10 1040-1053. MR0673642
-
(1982)
Ann. Statist
, vol.10
, pp. 1040-1053
-
-
STONE, C.J.1
-
25
-
-
0000629975
-
Cross-validatory choice and assessment of statistical predictions (with discussion)
-
MR0356377
-
STONE, M. (1974). Cross-validatory choice and assessment of statistical predictions (with discussion). J. Roy. Statist. Soc. Ser. B 36 111-147. MR0356377
-
(1974)
J. Roy. Statist. Soc. Ser. B
, vol.36
, pp. 111-147
-
-
STONE, M.1
-
27
-
-
50849093308
-
-
VAN DER LAAN, M. J., DUDOIT, S. and VAN DER VAART, A. W. (2006). The cross-validated adaptive epsilon-net estimator. Statist. Decisions 24, 373-395. MR2305113
-
VAN DER LAAN, M. J., DUDOIT, S. and VAN DER VAART, A. W. (2006). The cross-validated adaptive epsilon-net estimator. Statist. Decisions 24, 373-395. MR2305113
-
-
-
-
29
-
-
50849139667
-
-
WAHBA, G. (1990). Spline Models for Observational Data. SIAM, Philadelphia. MR1045442
-
WAHBA, G. (1990). Spline Models for Observational Data. SIAM, Philadelphia. MR1045442
-
-
-
-
30
-
-
50849133331
-
-
WEGKAMP, M. (2003). Model selection in nonparametric regression. Ann. Statist. 31252-273. MR1962506
-
WEGKAMP, M. (2003). Model selection in nonparametric regression. Ann. Statist. 31252-273. MR1962506
-
-
-
-
31
-
-
85017369930
-
-
WEISBERG, S. (2005). Applied Linear Regression, 3rd ed. Wiley, Hoboken, NJ. MR2112740
-
WEISBERG, S. (2005). Applied Linear Regression, 3rd ed. Wiley, Hoboken, NJ. MR2112740
-
-
-
-
32
-
-
0010378244
-
On the consistency of cross-validation in kernel nonparametric regression
-
MR0720259
-
WONG, W. H. (1983). On the consistency of cross-validation in kernel nonparametric regression. Ann. Statist., 11 1136-1141. MR0720259
-
(1983)
Ann. Statist
, vol.11
, pp. 1136-1141
-
-
WONG, W.H.1
-
33
-
-
1542573460
-
Adaptive regression by mixing
-
MR1946426
-
YANG, Y. (2001). Adaptive regression by mixing. J. Amer. Statist. Assoc. 96 574-588. MR1946426
-
(2001)
J. Amer. Statist. Assoc
, vol.96
, pp. 574-588
-
-
YANG, Y.1
-
34
-
-
0141573227
-
Regression with multiple candidate models: Selecting or mixing?
-
MR1997174
-
YANG, Y. (2003). Regression with multiple candidate models: Selecting or mixing? Statist. Sinica 13 783-809. MR1997174
-
(2003)
Statist. Sinica
, vol.13
, pp. 783-809
-
-
YANG, Y.1
-
35
-
-
21144472438
-
Model selection via multifold cross validation
-
MR1212178
-
ZHANG, P. (1993). Model selection via multifold cross validation. Ann. Statist. 21 299-313. MR1212178
-
(1993)
Ann. Statist
, vol.21
, pp. 299-313
-
-
ZHANG, P.1
|