-
1
-
-
0001835983
-
Thresholding of wavelet coefficients as multiple hypotheses testing procedure
-
Wavelets and Statistics. Springer, Berlin
-
ABRAMOVICH, F. and BENJAMINI, Y. (1995). Thresholding of wavelet coefficients as multiple hypotheses testing procedure. In Wavelets and Statistics. Lecture Notes in Statistics 103 5-14. Springer, Berlin.
-
(1995)
Lecture Notes in Statistics
, vol.103
, pp. 5-14
-
-
Abramovich, F.1
Benjamini, Y.2
-
2
-
-
33746242092
-
Adapting to unknown sparsity by controlling the false discovery rate
-
MR2281879
-
ABRAMOVICH, F., BENJAMINI, Y., DONOHO, D. L. and JOHNSTONE, I. M. (2006). Adapting to unknown sparsity by controlling the false discovery rate. Ann. Statist. 34 584-653. MR2281879
-
(2006)
Ann. Statist
, vol.34
, pp. 584-653
-
-
Abramovich, F.1
Benjamini, Y.2
Donoho, D.L.3
Johnstone, I.M.4
-
3
-
-
0016355478
-
A new look at the statistical model identification
-
System identification and time-series analysis. MR0423716
-
AKAIKE, H. (1974). A new look at the statistical model identification. IEEE Trans. Automat. Control AC-19 716-723. System identification and time-series analysis. MR0423716
-
(1974)
IEEE Trans. Automat. Control AC
, vol.19
, pp. 716-723
-
-
Akaike, H.1
-
4
-
-
0003495202
-
Statistical Inference Under Order Restrictions
-
Wiley, New York. MR0326887
-
BARLOW, R. E., BARTHOLOMEW, D. J., BREMNER, J. M. and BRUNK, H. D. (1972). Statistical Inference Under Order Restrictions. The Theory and Application of Isotonic Regression. Wiley, New York. MR0326887
-
(1972)
The Theory and Application of Isotonic Regression.
-
-
Barlow, R.E.1
Bartholomew, D.J.2
Bremner, J.M.3
Brunk, H.D.4
-
5
-
-
0002526114
-
Model selection by multiple test procedures
-
MR0921623
-
BAUER, P., PÖTSCHER, B. M. and HACKL, P. (1988). Model selection by multiple test procedures. Statistics 19 39-44. MR0921623
-
(1988)
Statistics
, vol.19
, pp. 39-44
-
-
Bauer, P.1
Pötscher, B.M.2
Hackl, P.3
-
6
-
-
85014561619
-
A fast iterative shrinkage-thresholding algorithm for linear inverse problems
-
MR2486527
-
BECK, A. and TEBOULLE, M. (2009). A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sci. 2 183-202. MR2486527
-
(2009)
SIAM J. Imaging Sci
, vol.2
, pp. 183-202
-
-
Beck, A.1
Teboulle, M.2
-
7
-
-
84856004485
-
Templates for convex cone problems with applications to sparse signal recovery
-
MR2833262
-
BECKER, S. R., CANDÈS, E. J. and GRANT, M. C. (2011). Templates for convex cone problems with applications to sparse signal recovery. Math. Program. Comput. 3 165-218. MR2833262
-
(2011)
Math. Program. Comput
, vol.3
, pp. 165-218
-
-
Becker, S.R.1
Candès, E.J.2
Grant, M.C.3
-
8
-
-
78650339300
-
A simple forward selection procedure based on false discovery rate control
-
MR2668704
-
BENJAMINI, Y. and GAVRILOV, Y. (2009). A simple forward selection procedure based on false discovery rate control. Ann. Appl. Stat. 3 179-198. MR2668704
-
(2009)
Ann. Appl. Stat
, vol.3
, pp. 179-198
-
-
Benjamini, Y.1
Gavrilov, Y.2
-
9
-
-
0001677717
-
Controlling the false discovery rate: A practical and powerful approach to multiple testing
-
MR1325392
-
BENJAMINI, Y. and HOCHBERG, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. Roy. Statist. Soc. Ser. B 57 289-300. MR1325392
-
(1995)
J. Roy. Statist. Soc. Ser. B
, vol.57
, pp. 289-300
-
-
Benjamini, Y.1
Hochberg, Y.2
-
10
-
-
14944365889
-
False discovery rate-adjusted multiple confidence intervals for selected parameters
-
MR2156820
-
BENJAMINI, Y. and YEKUTIELI, D. (2005). False discovery rate-adjusted multiple confidence intervals for selected parameters. J. Amer. Statist. Assoc. 100 71-93. MR2156820
-
(2005)
J. Amer. Statist. Assoc
, vol.100
, pp. 71-93
-
-
Benjamini, Y.1
Yekutieli, D.2
-
11
-
-
84879164483
-
Valid post-selection inference
-
MR3099122
-
BERK, R., BROWN, L., BUJA, A., ZHANG, K. and ZHAO, L. (2013). Valid post-selection inference. Ann. Statist. 41 802-837. MR3099122
-
(2013)
Ann. Statist
, vol.41
, pp. 802-837
-
-
Berk, R.1
Brown, L.2
Buja, A.3
Zhang, K.4
Zhao, L.5
-
12
-
-
34249957970
-
Active set algorithms for isotonic regression; a unifying framework
-
MR1068274
-
BEST, M. J. and CHAKRAVARTI, N. (1990). Active set algorithms for isotonic regression; a unifying framework. Math. Program. 47 425-439. MR1068274
-
(1990)
Math. Program
, vol.47
, pp. 425-439
-
-
Best, M.J.1
Chakravarti, N.2
-
14
-
-
84857648827
-
Asymptotic Bayesoptimality under sparsity of some multiple testing procedures
-
MR2850212
-
BOGDAN, M., CHAKRABARTI, A., FROMMLET, F. and GHOSH, J. K. (2011). Asymptotic Bayesoptimality under sparsity of some multiple testing procedures. Ann. Statist. 39 1551-1579. MR2850212
-
(2011)
Ann. Statist
, vol.39
, pp. 1551-1579
-
-
Bogdan, M.1
Chakrabarti, A.2
Frommlet, F.3
Ghosh, J.K.4
-
15
-
-
54949098146
-
Selecting explanatory variables with the modified version of Bayesian information criterion
-
BOGDAN, M., GHOSH, J. K. and ŻAK-SZATKOWSKA, M. (2008). Selecting explanatory variables with the modified version of Bayesian information criterion. Qual. Reliab. Eng. Int. 24 627-641.
-
(2008)
Qual. Reliab. Eng. Int.
, vol.24
, pp. 627-641
-
-
Bogdan, M.1
Ghosh, J.K.2
Żak-Szatkowska, M.3
-
16
-
-
84946556176
-
-
BOGDAN, M., VAN DEN BERG, E., SABATTI, C., SU, W. and CANDÈS, E. J. (2015). Supplement to "SLOPE-Adaptive variable selection via convex optimization." DOI:10.1214/15- AOAS842SUPP.
-
(2015)
Supplement to "SLOPE-Adaptive variable selection via convex optimization."
-
-
Bogdan, M.1
Van Den Berg, E.2
Sabatti, C.3
Su, W.4
Candès, E.J.5
-
18
-
-
39849102639
-
Simultaneous regression shrinkage, variable selection, and supervised clustering of predictors with OSCAR
-
MR2422825
-
BONDELL, H. D. and REICH, B. J. (2008). Simultaneous regression shrinkage, variable selection, and supervised clustering of predictors with OSCAR. Biometrics 64 115-123, 322-323. MR2422825
-
(2008)
Biometrics
, vol.64
, Issue.115-123
, pp. 322-323
-
-
Bondell, H.D.1
Reich, B.J.2
-
19
-
-
84885049881
-
Statistical significance in high-dimensional linear models
-
MR3102549
-
BÜHLMANN, P. (2013). Statistical significance in high-dimensional linear models. Bernoulli 19 1212-1242. MR3102549
-
(2013)
Bernoulli
, vol.19
, pp. 1212-1242
-
-
Bühlmann, P.1
-
20
-
-
34548275795
-
The Dantzig selector: Statistical estimation when p is much larger than n
-
MR2382644
-
CANDES, E. and TAO, T. (2007). The Dantzig selector: Statistical estimation when p is much larger than n. Ann. Statist. 35 2313-2351. MR2382644
-
(2007)
Ann. Statist
, vol.35
, pp. 2313-2351
-
-
Candes, E.1
Tao, T.2
-
21
-
-
57349174008
-
Enhancing sparsity by reweighted l1 minimization
-
MR2461611
-
CANDÈS, E. J., WAKIN, M. B. and BOYD, S. P. (2008). Enhancing sparsity by reweighted l1 minimization. J. Fourier Anal. Appl. 14 877-905. MR2461611
-
(2008)
J. Fourier Anal. Appl
, vol.14
, pp. 877-905
-
-
Candès, E.J.1
Wakin, M.B.2
Boyd, S.P.3
-
22
-
-
70450171127
-
Isotone optimization in R: Pool-adjacent-violators algorithm (PAVA) and active set methods
-
DE LEEUW, J.,HORNIK, K. andMAIR, P. (2009). Isotone optimization in R: Pool-adjacent-violators algorithm (PAVA) and active set methods. J. Stat. Softw. 32 1-24.
-
(2009)
J. Stat. Softw.
, vol.32
, pp. 1-24
-
-
De Leeuw, J.1
Hornik, K.2
Mair, P.3
-
23
-
-
84856005992
-
Tweedie's formula and selection bias
-
MR2896860
-
EFRON, B. (2011). Tweedie's formula and selection bias. J. Amer. Statist. Assoc. 106 1602-1614. MR2896860
-
(2011)
J. Amer. Statist. Assoc
, vol.106
, pp. 1602-1614
-
-
Efron, B.1
-
24
-
-
21844523862
-
The risk inflation criterion for multiple regression
-
MR1329177
-
FOSTER, D. P. and GEORGE, E. I. (1994). The risk inflation criterion for multiple regression. Ann. Statist. 22 1947-1975. MR1329177
-
(1994)
Ann. Statist
, vol.22
, pp. 1947-1975
-
-
Foster, D.P.1
George, E.I.2
-
25
-
-
0032680981
-
Local asymptotic coding and the minimum description length
-
MR1686271
-
FOSTER, D. P. and STINE, R. A. (1999). Local asymptotic coding and the minimum description length. IEEE Trans. Inform. Theory 45 1289-1293. MR1686271
-
(1999)
IEEE Trans. Inform. Theory
, vol.45
, pp. 1289-1293
-
-
Foster, D.P.1
Stine, R.A.2
-
26
-
-
85052356932
-
Controlling the false discovery rate via knockoffs
-
FOYGEL-BARBER, R. andCANDÈS, E. J. (2014). Controlling the false discovery rate via knockoffs. Ann. Statist. To appear. Available at arXiv:1404.5609.
-
(2014)
Ann. Statist. To appear.
-
-
Foygel-Barber, R.1
Candès, E.J.2
-
27
-
-
84884955624
-
Some optimality properties of FDR controlling rules under sparsity
-
MR3063610
-
FROMMLET, F. andBOGDAN, M. (2013). Some optimality properties of FDR controlling rules under sparsity. Electron. J. Stat. 7 1328-1368. MR3063610
-
(2013)
Electron. J. Stat
, vol.7
, pp. 1328-1368
-
-
Frommlet, F.1
Bogdan, M.2
-
28
-
-
79959746046
-
Modified versions of Bayesian information criterion for genome-wide association studies
-
MR2897552
-
FROMMLET, F., RUHALTINGER, F., TWARÓG, P. and BOGDAN, M. (2012). Modified versions of Bayesian information criterion for genome-wide association studies. Comput. Statist. Data Anal. 56 1038-1051. MR2897552
-
(2012)
Comput. Statist. Data Anal
, vol.56
, pp. 1038-1051
-
-
Frommlet, F.1
Ruhaltinger, F.2
Twaróg, P.3
Bogdan, M.4
-
30
-
-
0011598478
-
Projections onto order simplexes
-
MR0768632
-
GROTZINGER, S. J. andWITZGALL, C. (1984). Projections onto order simplexes. Appl. Math. Optim. 12 247-270. MR0768632
-
(1984)
Appl. Math. Optim
, vol.12
, pp. 247-270
-
-
Grotzinger, S.J.1
Witzgall, C.2
-
31
-
-
23744506754
-
Minimax detection of a signal for ln-balls
-
MR1680087
-
INGSTER, YU. I. (1998). Minimax detection of a signal for ln-balls. Math. Methods Statist. 7 401- 428. MR1680087
-
(1998)
Math. Methods Statist
, vol.7
, pp. 401-428
-
-
Ingster Yu, I.1
-
32
-
-
84919709419
-
Confidence intervals and hypothesis testing for high-dimensional regression
-
MR3277152
-
JAVANMARD, A. and MONTANARI, A. (2014a). Confidence intervals and hypothesis testing for high-dimensional regression. J. Mach. Learn. Res. 15 2869-2909. MR3277152
-
(2014)
J. Mach. Learn. Res
, vol.15
, pp. 2869-2909
-
-
Javanmard, A.1
Montanari, A.2
-
33
-
-
84907212736
-
Hypothesis testing in high-dimensional regression under the Gaussian random design model: Asymptotic theory
-
MR3265038
-
JAVANMARD, A. andMONTANARI, A. (2014b). Hypothesis testing in high-dimensional regression under the Gaussian random design model: Asymptotic theory. IEEE Trans. Inform. Theory 60 6522-6554. MR3265038
-
(2014)
IEEE Trans. Inform. Theory
, vol.60
, pp. 6522-6554
-
-
Javanmard, A.1
Montanari, A.2
-
34
-
-
24944533365
-
Nonmetric multidimensional scaling: A numerical method
-
MR0169713
-
KRUSKAL, J. B. (1964). Nonmetric multidimensional scaling: A numerical method. Psychometrika 29 115-129. MR0169713
-
(1964)
Psychometrika
, vol.29
, pp. 115-129
-
-
Kruskal, J.B.1
-
35
-
-
84901725294
-
A significance test for the Lasso
-
MR3210970
-
LOCKHART, R., TAYLOR, J., TIBSHIRANI, R. J. and TIBSHIRANI, R. (2014). A significance test for the Lasso. Ann. Statist. 42 413-468. MR3210970
-
(2014)
Ann. Statist
, vol.42
, pp. 413-468
-
-
Lockhart, R.1
Taylor, J.2
Tibshirani, R.J.3
Tibshirani, R.4
-
36
-
-
84915425007
-
Some comments on cp
-
MALLOWS, C. L. (1973). Some comments on cp. Technometrics 15 661-676.
-
(1973)
Technometrics
, vol.15
, pp. 661-676
-
-
Mallows, C.L.1
-
40
-
-
77954796034
-
Introductory Lectures on Convex Optimization
-
Kluwer Academic, Boston, MA. MR2142598
-
NESTEROV, Y. (2004). Introductory Lectures on Convex Optimization. A Basic Course. Kluwer Academic, Boston, MA. MR2142598
-
(2004)
A Basic Course.
-
-
Nesterov, Y.1
-
41
-
-
67651063011
-
Gradient methods for minimizing composite objective function
-
Center for Operations Research and Econometrics (CORE), Université Catholique de Louvain
-
NESTEROV, Y. (2007). Gradient methods for minimizing composite objective function. CORE discussion paper. Center for Operations Research and Econometrics (CORE), Université Catholique de Louvain. Available at http://www.ecore.be/DPs/dp_1191313936.pdf.
-
(2007)
CORE discussion paper.
-
-
Nesterov, Y.1
-
42
-
-
84884129062
-
-
Foundations and Trends in Optimization
-
PARIKH, N. and BOYD, S. (2013). Proximal algorithms. In Foundations and Trends in Optimization 1 123-231.
-
(2013)
Proximal algorithms.
, vol.1
, pp. 123-231
-
-
Parikh, N.1
Boyd, S.2
-
43
-
-
0036101887
-
Some results on false discovery rate in stepwise multiple testing procedures
-
MR1892663
-
SARKAR, S. K. (2002). Some results on false discovery rate in stepwise multiple testing procedures. Ann. Statist. 30 239-257. MR1892663
-
(2002)
Ann. Statist
, vol.30
, pp. 239-257
-
-
Sarkar, S.K.1
-
44
-
-
84896701941
-
Re-sequencing expands our understanding of the phenotypic impact of variants at GWAS loci
-
SERVICE, S. K., TESLOVICH, T. M., FUCHSBERGER, C., RAMENSKY, V., YAJNIK, P., KOBOLDT, D. C., LARSON, D. E., ZHANG, Q., LIN, L., WELCH, R., DING, L., MCLELLAN, M. D., O'LAUGHLIN, M., FRONICK, C., FULTON, L. L.,MAGRINI, V., SWIFT, A., ELLIOTT, P., JARVELIN, M. R., KAAKINEN, M.,MCCARTHY, M. I., PELTONEN, L., POUTA, A., BONNYCASTLE, L. L., COLLINS, F. S., NARISU, N., STRINGHAM, H. M., TUOMILEHTO, J., RIPATTI, S., FULTON, R. S., SABATTI, C., WILSON, R. K., BOEHNKE, M. and FREIMER, N. B. (2014). Re-sequencing expands our understanding of the phenotypic impact of variants at GWAS loci. PLoS Genet. 10 e1004147.
-
(2014)
PLoS Genet.
, vol.10
-
-
Service, S.K.1
Teslovich, T.M.2
Fuchsberger, C.3
Ramensky, V.4
Yajnik, P.5
Koboldt, D.C.6
Larson, D.E.7
Zhang, Q.8
Lin, L.9
Welch, R.10
Ding, L.11
McLellan, M.D.12
O'laughlin, M.13
Fronick, C.14
Fulton, L.L.15
Magrini, V.16
Swift, A.17
Elliott, P.18
Jarvelin, M.R.19
Kaakinen, M.20
McCarthy, M.I.21
Peltonen, L.22
Pouta, A.23
Bonnycastle, L.L.24
Collins, F.S.25
Narisu, N.26
Stringham, H.M.27
Tuomilehto, J.28
Ripatti, S.29
Fulton, R.S.30
Sabatti, C.31
Wilson, R.K.32
Boehnke, M.33
Freimer, N.B.34
more..
-
46
-
-
84869449202
-
Scaled sparse linear regression
-
MR2999166
-
SUN, T. and ZHANG, C.-H. (2012). Scaled sparse linear regression. Biometrika 99 879-898. MR2999166
-
(2012)
Biometrika
, vol.99
, pp. 879-898
-
-
Sun, T.1
Zhang, C.-H.2
-
47
-
-
85194972808
-
Regression shrinkage and selection via the Lasso
-
MR1379242
-
TIBSHIRANI, R. (1996). Regression shrinkage and selection via the Lasso. J. Roy. Statist. Soc. Ser. B 58 267-288. MR1379242
-
(1996)
J. Roy. Statist. Soc. Ser. B
, vol.58
, pp. 267-288
-
-
Tibshirani, R.1
-
48
-
-
0039724913
-
The covariance inflation criterion for adaptive model selection
-
MR1707859
-
TIBSHIRANI, R. and KNIGHT, K. (1999). The covariance inflation criterion for adaptive model selection. J. R. Stat. Soc. Ser. B. Stat. Methodol. 61 529-546. MR1707859
-
(1999)
J. R. Stat. Soc. Ser. B. Stat. Methodol
, vol.61
, pp. 529-546
-
-
Tibshirani, R.1
Knight, K.2
-
49
-
-
84988001472
-
On asymptotically optimal confidence regions and tests for high-dimensional models
-
MR3224285
-
VAN DE GEER, S., BÜHLMANN, P., RITOV, Y. and DEZEURE, R. (2014). On asymptotically optimal confidence regions and tests for high-dimensional models. Ann. Statist. 42 1166-1202. MR3224285
-
(2014)
Ann. Statist
, vol.42
, pp. 1166-1202
-
-
Van De Geer, S.1
Bühlmann, P.2
Ritov, Y.3
Dezeure, R.4
-
50
-
-
69049091975
-
High-dimensional variable selection
-
MR2543689
-
WASSERMAN, L. and ROEDER, K. (2009). High-dimensional variable selection. Ann. Statist. 37 2178-2201. MR2543689
-
(2009)
Ann. Statist
, vol.37
, pp. 2178-2201
-
-
Wasserman, L.1
Roeder, K.2
-
51
-
-
84878037001
-
Model selection and sharp asymptotic minimaxity
-
MR3055256
-
WU, Z. and ZHOU, H. H. (2013).Model selection and sharp asymptotic minimaxity. Probab. Theory Related Fields 156 165-191. MR3055256
-
(2013)
Probab. Theory Related Fields
, vol.156
, pp. 165-191
-
-
Wu, Z.1
Zhou, H.H.2
-
52
-
-
84903649808
-
Decreasing weighted sorted l1 regularization
-
ZENG, X. and FIGUEIREDO, M. (2014). Decreasing weighted sorted l1 regularization. IEEE Signal Process. Lett. 1240-1244.
-
(2014)
IEEE Signal Process. Lett
, pp. 1240-1244
-
-
Zeng, X.1
Figueiredo, M.2
-
53
-
-
84891835103
-
Confidence intervals for low dimensional parameters in high dimensional linear models
-
MR3153940
-
ZHANG, C.-H. and ZHANG, S. S. (2014). Confidence intervals for low dimensional parameters in high dimensional linear models. J. R. Stat. Soc. Ser. B. Stat. Methodol. 76 217-242. MR3153940
-
(2014)
J. R. Stat. Soc. Ser. B. Stat. Methodol
, vol.76
, pp. 217-242
-
-
Zhang, C.-H.1
Zhang, S.S.2
-
54
-
-
84876117777
-
Efficient sparse modeling with automatic feature grouping
-
ZHONG, L. and KWOK, J. (2012). Efficient sparse modeling with automatic feature grouping. IEEE Trans. Neural Netw. Learn. Syst. 1436-1447.
-
(2012)
IEEE Trans. Neural Netw. Learn. Syst.
, pp. 1436-1447
-
-
Zhong, L.1
Kwok, J.2
-
55
-
-
33846114377
-
The adaptive Lasso and its oracle properties
-
MR2279469
-
ZOU, H. (2006). The adaptive Lasso and its oracle properties. J. Amer. Statist. Assoc. 101 1418-1429. MR2279469
-
(2006)
J. Amer. Statist. Assoc
, vol.101
, pp. 1418-1429
-
-
Zou, H.1
|