-
1
-
-
69949186291
-
Identifiability of parameters in latent structure models with many observed variables
-
ALLMAN, E. S., MATIAS, C. & RHODES, J. A. (2009). Identifiability of parameters in latent structure models with many observed variables. Ann. Statist. 37, 3099-132.
-
(2009)
Ann. Statist.
, vol.37
, pp. 3099-3132
-
-
Allman, E.S.1
Matias, C.2
Rhodes, J.A.3
-
2
-
-
0001497505
-
Estimating linear restrictions on regression coefficients for multivariate normal distributions
-
ANDERSON, T. W. (1951). Estimating linear restrictions on regression coefficients for multivariate normal distributions. Ann. Math. Statist. 22, 327-51.
-
(1951)
Ann. Math. Statist.
, vol.22
, pp. 327-351
-
-
Anderson, T.W.1
-
3
-
-
0033236914
-
Asymptotic distribution of the reduced rank regression estimator under general conditions
-
ANDERSON, T. W. (1999). Asymptotic distribution of the reduced rank regression estimator under general conditions. Ann. Statist. 27, 1141-54.
-
(1999)
Ann. Statist.
, vol.27
, pp. 1141-1154
-
-
Anderson, T.W.1
-
4
-
-
0347985232
-
Reduced rank regression in cointegrated models
-
ANDERSON, T. W. (2002a). Reduced rank regression in cointegrated models. J. Economet. 106, 203-16.
-
(2002)
J. Economet.
, vol.106
, pp. 203-216
-
-
Anderson, T.W.1
-
5
-
-
34548412340
-
Specification and misspecification in reduced rank regression
-
ANDERSON, T. W. (2002b). Specification and misspecification in reduced rank regression. Sankhya A 64, 193-205.
-
(2002)
Sankhya A
, vol.64
, pp. 193-205
-
-
Anderson, T.W.1
-
7
-
-
0000927638
-
Predicting multivariate responses in multiple linear regression
-
BREIMAN, L. & FRIEDMAN, J. H. (1997). Predicting multivariate responses in multiple linear regression. J. R. Statist. Soc. B 59, 3-37.
-
(1997)
J. R. Statist. Soc. B
, vol.59
, pp. 3-37
-
-
Breiman, L.1
Friedman, J.H.2
-
8
-
-
82655182661
-
Optimal selection of reduced rank estimators of high-dimensional matrices
-
BUNEA, F., SHE, Y. & WEGKAMP, M. H. (2011). Optimal selection of reduced rank estimators of high-dimensional matrices. Ann. Statist. 39, 1282-309.
-
(2011)
Ann. Statist.
, vol.39
, pp. 1282-1309
-
-
Bunea, F.1
She, Y.2
Wegkamp, M.H.3
-
9
-
-
84873329281
-
Joint variable and rank selection for parsimonious estimation of high-dimensional matrices
-
BUNEA, F., SHE, Y. & WEGKAMP, M. H. (2012). Joint variable and rank selection for parsimonious estimation of high-dimensional matrices. Ann. Statist. 40, 2359-88.
-
(2012)
Ann. Statist.
, vol.40
, pp. 2359-2388
-
-
Bunea, F.1
She, Y.2
Wegkamp, M.H.3
-
10
-
-
84858281659
-
Reduced-rank stochastic regression with a sparse singular value decomposition
-
CHEN, K., CHAN, K. S. & STENSETH, N. R. (2012). Reduced-rank stochastic regression with a sparse singular value decomposition. J. R. Statist. Soc. B 74, 203-21.
-
(2012)
J. R. Statist. Soc. B
, vol.74
, pp. 203-221
-
-
Chen, K.1
Chan, K.S.2
Stenseth, N.R.3
-
11
-
-
84890351391
-
Reduced rank regression via adaptive nuclear norm penalization
-
CHEN, K., DONG, H. & CHAN, K.-S. (2013). Reduced rank regression via adaptive nuclear norm penalization. Biometrika 100, 901-20.
-
(2013)
Biometrika
, vol.100
, pp. 901-920
-
-
Chen, K.1
Dong, H.2
Chan, K.-S.3
-
12
-
-
84871942172
-
Sparse reduced-rank regression for simultaneous dimension reduction and variable selection
-
CHEN, L. & HUANG, J. Z. (2012). Sparse reduced-rank regression for simultaneous dimension reduction and variable selection. J. Am. Statist. Assoc. 107, 1533-45.
-
(2012)
J. Am. Statist. Assoc.
, vol.107
, pp. 1533-1545
-
-
Chen, L.1
Huang, J.Z.2
-
13
-
-
0003908675
-
-
New York: Springer, 3rd ed
-
COX, D. A., LITTLE, J. & O'SHEA, D. (2007). Ideals, Varieties, and Algorithms: An Introduction to Computational Algebraic Geometry and Commutative Algebra. New York: Springer, 3rd ed.
-
(2007)
Ideals, Varieties, and Algorithms: An Introduction to Computational Algebraic Geometry and Commutative Algebra
-
-
Cox, D.A.1
Little, J.2
O'Shea, D.3
-
14
-
-
0001495113
-
Procedures for reduced-rank regression
-
DAVIES, P. T. & TSO, M. K.-S. (1982). Procedures for reduced-rank regression. Appl. Statist. 31, 244-55.
-
(1982)
Appl. Statist.
, vol.31
, pp. 244-255
-
-
Davies, P.T.1
Tso, M.K.-S.2
-
15
-
-
84950459514
-
Adapting to unknown smoothness via wavelet shrinkage
-
DONOHO, D. & JOHNSTONE, I. (1995). Adapting to unknown smoothness via wavelet shrinkage. J. Am. Statist. Assoc. 90, 1200-24.
-
(1995)
J. Am. Statist. Assoc.
, vol.90
, pp. 1200-1224
-
-
Donoho, D.1
Johnstone, I.2
-
16
-
-
0000802374
-
The approximation of one matrix by another of lower rank
-
ECKART, C. & YOUNG, G. (1936). The approximation of one matrix by another of lower rank. Psychometrika 1, 211-8.
-
(1936)
Psychometrika
, vol.1
, pp. 211-218
-
-
Eckart, C.1
Young, G.2
-
17
-
-
4944239996
-
The estimation of prediction error: Covariance penalties and cross-validation (with Comments, Rejoinder
-
EFRON, B., BURMAN, P., DENBY, L., LANDWEHR, J. M., MALLOWS, C. L., SHEN, X., HUANG, H.-C., YE, J.&ZHANG, C. (2004). The estimation of prediction error: Covariance penalties and cross-validation (with Comments, Rejoinder). J. Am. Statist. Assoc. 99, 619-42.
-
(2004)
J. Am. Statist. Assoc.
, vol.99
, pp. 619-642
-
-
Efron, B.1
Burman, P.2
Denby, L.3
Landwehr, J.M.4
Mallows, C.L.5
Shen, X.6
Huang, H.-C.7
Ye, J.8
Zhang, C.9
-
18
-
-
32044449925
-
Generalized cross-validation as a method for choosing a good ridge parameter
-
GOLUB, G., HEATH, M. & WAHBA, G. (1979). Generalized cross-validation as a method for choosing a good ridge parameter. Technometrics 21, 215-23.
-
(1979)
Technometrics
, vol.21
, pp. 215-223
-
-
Golub, G.1
Heath, M.2
Wahba, G.3
-
21
-
-
0003684449
-
-
New York: Springer
-
HASTIE, T. J., TIBSHIRANI, R. J. & FRIEDMAN, J. H. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer.
-
(2009)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
-
-
Hastie, T.J.1
Tibshirani, R.J.2
Friedman, J.H.3
-
22
-
-
84946633097
-
Selection of the best subset in regression analysis
-
HOCKING, R. R. & LESLIE, R. N. (1967). Selection of the best subset in regression analysis. Technometrics 9, 531-40.
-
(1967)
Technometrics
, vol.9
, pp. 531-540
-
-
Hocking, R.R.1
Leslie, R.N.2
-
23
-
-
0001523230
-
The most predictable criterion
-
HOTELLING, H. (1935). The most predictable criterion. J. Educ. Psychol. 26, 139-42.
-
(1935)
J. Educ. Psychol.
, vol.26
, pp. 139-142
-
-
Hotelling, H.1
-
24
-
-
0016511949
-
Reduced-rank regression for the multivariate linear model
-
IZENMAN, A. J. (1975). Reduced-rank regression for the multivariate linear model. J. Mult. Statist. 5, 248-64.
-
(1975)
J. Mult. Statist.
, vol.5
, pp. 248-264
-
-
Izenman, A.J.1
-
27
-
-
34248594305
-
Multivariate reduced-rank nonlinear time series modeling
-
LI, M. C. & CHAN, K. S. (2007).Multivariate reduced-rank nonlinear time series modeling. Statist. Sinica 17, 139-59.
-
(2007)
Statist. Sinica
, vol.17
, pp. 139-159
-
-
Li, M.C.1
Chan, K.S.2
-
28
-
-
41949088050
-
L1-norm quantile regression
-
LI, Y. & ZHU, J. (2008). L1-norm quantile regression. J. Comp. Graph. Statist. 17, 163-85.
-
(2008)
J. Comp. Graph. Statist.
, vol.17
, pp. 163-185
-
-
Li, Y.1
Zhu, J.2
-
29
-
-
84857638087
-
Convex optimization methods for dimension reduction and coefficient estimation in multivariate linear regression
-
LU, Z., MONTEIRO, R. & YUAN, M. (2012). Convex optimization methods for dimension reduction and coefficient estimation in multivariate linear regression. Math. Programming 131, 163-94.
-
(2012)
Math. Programming
, vol.131
, pp. 163-194
-
-
Lu, Z.1
Monteiro, R.2
Yuan, M.3
-
31
-
-
84915425007
-
Some comments on Cp
-
MALLOWS, C. L. (1973). Some comments on Cp. Technometrics 15, 661-75.
-
(1973)
Technometrics
, vol.15
, pp. 661-675
-
-
Mallows, C.L.1
-
32
-
-
0000957593
-
Principal components regression with exploratory statistical research
-
MASSY, W. F. (1965). Principal components regression with exploratory statistical research. J. Am. Statist. Assoc. 60, 234-46.
-
(1965)
J. Am. Statist. Assoc.
, vol.60
, pp. 234-246
-
-
Massy, W.F.1
-
33
-
-
0034237944
-
On the degrees of freedom in shape-restricted regression
-
MEYER, M. & WOODROOFE, M. (2000). On the degrees of freedom in shape-restricted regression. Ann. Statist. 28, 1083-104.
-
(2000)
Ann. Statist.
, vol.28
, pp. 1083-1104
-
-
Meyer, M.1
Woodroofe, M.2
-
34
-
-
0000178613
-
On the reciprocal of the general algebraic matrix
-
MOORE, E. H. (1920). On the reciprocal of the general algebraic matrix. Bull. Am. Math. Soc. 26, 394-5.
-
(1920)
Bull. Am. Math. Soc.
, vol.26
, pp. 394-395
-
-
Moore, E.H.1
-
35
-
-
82055164253
-
Reduced rank ridge regression and its kernel extensions
-
MUKHERJEE, A. & ZHU, J. (2011). Reduced rank ridge regression and its kernel extensions. Statist. Anal. Data Mining 4, 612-22.
-
(2011)
Statist. Anal. Data Mining
, vol.4
, pp. 612-622
-
-
Mukherjee, A.1
Zhu, J.2
-
36
-
-
79952934740
-
Estimation of (near) low-rank matrices with noise and high-dimensional scaling
-
NEGHABAN, S. &WAINWRIGHT, M. J. (2011). Estimation of (near) low-rank matrices with noise and high-dimensional scaling. Ann. Statist. 39, 1069-97.
-
(2011)
Ann. Statist.
, vol.39
, pp. 1069-1097
-
-
Neghaban, S.1
Wainwright, M.J.2
-
37
-
-
33646253883
-
Critical points of the singular value decomposition
-
O'NEIL, K. (2005). Critical points of the singular value decomposition. SIAM J. Matrix Anal. Appl. 27, 459-73.
-
(2005)
SIAM J. Matrix Anal. Appl.
, vol.27
, pp. 459-473
-
-
O'Neil, K.1
-
38
-
-
84947145047
-
A generalized inverse for matrices
-
PENROSE, R. (1955). A generalized inverse for matrices. Proc. Camb. Phil. Soc. 51, 406-13.
-
(1955)
Proc. Camb. Phil. Soc.
, vol.51
, pp. 406-413
-
-
Penrose, R.1
-
39
-
-
0006580818
-
Matrix approximations and reduction of dimensionality in multivariate statistical analysis
-
P. R. Krishnaiah, Ed. Amsterdam: North-Holland
-
RAO, C. R. (1978).Matrix approximations and reduction of dimensionality in multivariate statistical analysis. In Proc. 5th Int. Symp. Mult. Anal., P. R. Krishnaiah, ed. Amsterdam: North-Holland, pp. 3-22.
-
(1978)
Proc. 5th Int. Symp. Mult. Anal.
, pp. 3-22
-
-
Rao, C.R.1
-
41
-
-
79952902758
-
Estimation of high-dimensional low-rank matrices
-
ROHDE, A. & TSYBAKOV, A. B. (2011). Estimation of high-dimensional low-rank matrices. Ann. Statist. 39, 887-930.
-
(2011)
Ann. Statist.
, vol.39
, pp. 887-930
-
-
Rohde, A.1
Tsybakov, A.B.2
-
42
-
-
0000120766
-
Estimating the dimension of a model
-
SCHWARZ, G. (1978). Estimating the dimension of a model. Ann. Statist. 6, 461-4.
-
(1978)
Ann. Statist.
, vol.6
, pp. 461-464
-
-
Schwarz, G.1
-
43
-
-
79952701411
-
Thresholding-based iterative selection procedures for model selection and shrinkage
-
SHE, Y. (2009). Thresholding-based iterative selection procedures for model selection and shrinkage. Electron. J. Statist. 3, 384-415.
-
(2009)
Electron. J. Statist.
, vol.3
, pp. 384-415
-
-
She, Y.1
-
44
-
-
84880174018
-
Reduced rank vector generalized linear models for feature extraction
-
SHE, Y. (2013). Reduced rank vector generalized linear models for feature extraction. Statist. Infer. 6, 197-209.
-
(2013)
Statist. Infer.
, vol.6
, pp. 197-209
-
-
She, Y.1
-
45
-
-
0036489055
-
Adaptive model selection
-
SHEN, X. & YE, J. (2002). Adaptive model selection. J. Am. Statist. Assoc. 97, 210-21.
-
(2002)
J. Am. Statist. Assoc.
, vol.97
, pp. 210-221
-
-
Shen, X.1
Ye, J.2
-
46
-
-
0000169918
-
Estimation of the mean of a multivariate normal distribution
-
STEIN, C. M. (1981). Estimation of the mean of a multivariate normal distribution. Ann. Statist. 9, 1135-51.
-
(1981)
Ann. Statist.
, vol.9
, pp. 1135-1151
-
-
Stein, C.M.1
-
47
-
-
85194972808
-
Regression shrinkage and selection via the lasso
-
TIBSHIRANI, R. (1996). Regression shrinkage and selection via the lasso. J. R. Statist. Soc. B 58, 267-88.
-
(1996)
J. R. Statist. Soc. B
, vol.58
, pp. 267-288
-
-
Tibshirani, R.1
-
48
-
-
84872012577
-
Degrees of freedom in lasso problems
-
TIBSHIRANI, R. J. & TAYLOR, J. (2011). Degrees of freedom in lasso problems. Ann. Statist. 40, 1198-232.
-
(2011)
Ann. Statist.
, vol.40
, pp. 1198-1232
-
-
Tibshirani, R.J.1
Taylor, J.2
-
49
-
-
54049093683
-
Admissibility and minimaxity of Bayes estimators for a normal mean matrix
-
TSUKUMA, H. (2008). Admissibility and minimaxity of Bayes estimators for a normal mean matrix. J. Mult. Anal. 99, 2251-64.
-
(2008)
J. Mult. Anal.
, vol.99
, pp. 2251-2264
-
-
Tsukuma, H.1
-
50
-
-
0012538727
-
Reduced rank models with two sets of regressors
-
VELU, R. (1991). Reduced rank models with two sets of regressors. Appl. Statist. 40, 159-70.
-
(1991)
Appl. Statist.
, vol.40
, pp. 159-170
-
-
Velu, R.1
-
51
-
-
22044448669
-
Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana
-
WILLE, A., ZIMMERMANN, P., VRANOVA, E., FÜRHOLZ, A., LAULE, O., BLEULER, S., HENNIG, L., PRELIC, A., VON ROHR, P., THIELE, L., ZITZLER, E., GRUISSEM, W. & BÜHLMANN, P. (2004). Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana. Genome Biol. 5, 1-13.
-
(2004)
Genome Biol.
, vol.5
, pp. 1-13
-
-
Wille, A.1
Zimmermann, P.2
Vranova, E.3
Fürholz, A.4
Laule, O.5
Bleuler, S.6
Hennig, L.7
Prelic, A.8
Von Rohr, P.9
Thiele, L.10
Zitzler, E.11
Gruissem, W.12
Bühlmann, P.13
-
52
-
-
70149096300
-
A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
-
WITTEN, D. M., TIBSHIRANI, R. J. & HASTIE, T. J. (2009). A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 10, 515-34.
-
(2009)
Biostatistics
, vol.10
, pp. 515-534
-
-
Witten, D.M.1
Tibshirani, R.J.2
Hastie, T.J.3
-
53
-
-
0002692783
-
Soft modeling by latent variables: The nonlinear iterative partial least squares approach
-
Papers in Honour of M. S. Bartlett, J. Gani, ed. London: Academic Press
-
WOLD, H. (1975). Soft modeling by latent variables: The nonlinear iterative partial least squares approach. In Perspectives in Probability and Statistics. Papers in Honour of M. S. Bartlett, J. Gani, ed. London: Academic Press.
-
(1975)
Perspectives in Probability and Statistics
-
-
Wold, H.1
-
54
-
-
0032351389
-
On measuring and correcting the effects of data mining and model selection
-
YE, J. (1998). On measuring and correcting the effects of data mining and model selection. J. Am. Statist. Assoc. 93, 120-31.
-
(1998)
J. Am. Statist. Assoc.
, vol.93
, pp. 120-131
-
-
Ye, J.1
-
55
-
-
84993729357
-
Reduced rank vector generalized linear models
-
YEE, T. & HASTIE, T. J. (2003). Reduced rank vector generalized linear models. Statist. Mod. 3, 15-41.
-
(2003)
Statist. Mod.
, vol.3
, pp. 15-41
-
-
Yee, T.1
Hastie, T.J.2
-
56
-
-
34249004618
-
Dimension reduction and coefficient estimation in multivariate linear regression
-
YUAN, M., EKICI, A., LU, Z. & MONTEIRO, R. (2007). Dimension reduction and coefficient estimation in multivariate linear regression. J. R. Statist. Soc. B 69, 329-46.
-
(2007)
J. R. Statist. Soc. B
, vol.69
, pp. 329-346
-
-
Yuan, M.1
Ekici, A.2
Lu, Z.3
Monteiro, R.4
-
57
-
-
34548536008
-
On the "degrees of freedom" of the lasso
-
ZOU, H., HASTIE, T. J.&TIBSHIRANI, R. J. (2007). On the "degrees of freedom" of the lasso. Ann. Statist. 35, 2173-92.
-
(2007)
Ann. Statist.
, vol.35
, pp. 2173-2192
-
-
Zou, H.1
Hastie, T.J.2
Tibshirani, R.J.3
|