메뉴 건너뛰기




Volumn 23, Issue 1, 2013, Pages 119-143

Generalized double pareto shrinkage

Author keywords

Heavy tails; High dimensional data; LASSO; Maximum a posteriori estimation; Relevance vector machine; Robust prior; Shrinkage estimation

Indexed keywords


EID: 84878094378     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: 10.5705/ss.2011.048     Document Type: Article
Times cited : (282)

References (40)
  • 1
    • 0011564321 scopus 로고
    • A robust generalized Bayes estimator and confidence region for a multivariate normal mean
    • Berger, J. (1980). A robust generalized Bayes estimator and confidence region for a multivariate normal mean. Ann. Statist. 8, 716-761.
    • (1980) Ann. Statist. , vol.8 , pp. 716-761
    • Berger, J.1
  • 3
    • 0030344230 scopus 로고    scopus 로고
    • Heuristics of instability and stabilization in model selection
    • Breiman, L. (1996). Heuristics of instability and stabilization in model selection. Ann. Statist. 24, 2350-2383.
    • (1996) Ann. Statist. , vol.24 , pp. 2350-2383
    • Breiman, L.1
  • 4
    • 84950771789 scopus 로고
    • Estimating optimal transformations for multiple regression and correlation
    • Breiman, L. and Friedman, J. H. (1985), Estimating optimal transformations for multiple regression and correlation. J. Amer. Statist. Assoc. 80, 580-598.
    • (1985) J. Amer. Statist. Assoc. , vol.80 , pp. 580-598
    • Breiman, L.1    Friedman, J.H.2
  • 7
    • 77952811536 scopus 로고    scopus 로고
    • The horseshoe estimator for sparse signals
    • Carvalho, C., Polson, N. and Scott, J. (2010). The horseshoe estimator for sparse signals. Biometrika 97, 465-480.
    • (2010) Biometrika , vol.97 , pp. 465-480
    • Carvalho, C.1    Polson, N.2    Scott, J.3
  • 10
    • 79952794262 scopus 로고    scopus 로고
    • Bayesian adaptive sampling for variable selection and model averaging
    • Clyde, M., Ghosh, J. and Littman, M. L. (2010). Bayesian adaptive sampling for variable selection and model averaging. J. Comput. Graph. Statist. 20, 80-101.
    • (2010) J. Comput. Graph. Statist. , vol.20 , pp. 80-101
    • Clyde, M.1    Ghosh, J.2    Littman, M.L.3
  • 14
    • 1542784498 scopus 로고    scopus 로고
    • Variable selection via nonconcave penalized likelihood and its oracle properties
    • Fan, J. and Li, R. (2001). Variable selection via nonconcave penalized likelihood and its oracle properties. J. Amer. Statist. Assoc. 96, 1348-1360.
    • (2001) J. Amer. Statist. Assoc. , vol.96 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 16
    • 0032361278 scopus 로고    scopus 로고
    • Penalized regressions: The bridge versus the lasso
    • Fu, W. (1998). Penalized regressions: The bridge versus the lasso. J. Comput. Graph. Statist. 7, 397-416.
    • (1998) J. Comput. Graph. Statist. , vol.7 , pp. 397-416
    • Fu, W.1
  • 18
    • 21844523306 scopus 로고
    • On the asymptotics of constrained M-estimation
    • Geyer, C. J. (1994). On the asymptotics of constrained M-estimation. Ann. Statist. 22, 1993-2010.
    • (1994) Ann. Statist. , vol.22 , pp. 1993-2010
    • Geyer, C.J.1
  • 19
    • 84884265048 scopus 로고    scopus 로고
    • Estimation for multivariate normal and Student-t data with monotone missingness
    • Gramacy, R. B. (2010). Estimation for multivariate normal and Student-t data with monotone missingness - Monomvn package manual.
    • (2010) Monomvn Package Manual
    • Gramacy, R.B.1
  • 20
    • 48249133172 scopus 로고    scopus 로고
    • Bayesian adaptive lassos with non-convex penalization
    • Griffin, J. E. and Brown, P. J. (2007). Bayesian adaptive lassos with non-convex penalization. Technical Report.
    • (2007) Technical Report
    • Griffin, J.E.1    Brown, P.J.2
  • 21
    • 78650337471 scopus 로고    scopus 로고
    • Inference with normal-gamma prior distributions in regression problems
    • Griffin, J. E. and Brown, P. J. (2010). Inference with normal-gamma prior distributions in regression problems. Bayesian Anal. 5, 171-188.
    • (2010) Bayesian Anal. , vol.5 , pp. 171-188
    • Griffin, J.E.1    Brown, P.J.2
  • 22
    • 71249130909 scopus 로고    scopus 로고
    • Bayesian lasso regression
    • Hans, C. (2009). Bayesian lasso regression. Biometrika 96, 835-845.
    • (2009) Biometrika , vol.96 , pp. 835-845
    • Hans, C.1
  • 24
    • 0034287156 scopus 로고    scopus 로고
    • Asymptotics for lasso-type estimators
    • Knight, K. and Fu, W. (2000). Asymptotics for lasso-type estimators. Ann. Statist. 28, 1356-1378.
    • (2000) Ann. Statist. , vol.28 , pp. 1356-1378
    • Knight, K.1    Fu, W.2
  • 25
    • 84857759953 scopus 로고    scopus 로고
    • Bayesian sparsity-path-analysis of genetic association signal using generalized t priors
    • Lee, A., Caron, F., Doucet, A. and Holmes, C. (2012). Bayesian sparsity-path-analysis of genetic association signal using generalized t priors. Statist. Appl. Genet. Mol. Biol. 11.
    • (2012) Statist. Appl. Genet. Mol. Biol. , pp. 11
    • Lee, A.1    Caron, F.2    Doucet, A.3    Holmes, C.4
  • 27
    • 84974220416 scopus 로고
    • Partially adaptive estimation of regression models via the generalized t distribution
    • McDonald, J. B. and Newey, W. K. (1988). Partially adaptive estimation of regression models via the generalized t distribution. Econom. Theory 4, 428-457.
    • (1988) Econom. Theory , vol.4 , pp. 428-457
    • McDonald, J.B.1    Newey, W.K.2
  • 29
    • 0001075431 scopus 로고
    • Statistical inference using extreme order statistics
    • Pickands, J. (1975). Statistical inference using extreme order statistics. Ann. Statist. 3, 119-131.
    • (1975) Ann. Statist. , vol.3 , pp. 119-131
    • Pickands, J.1
  • 30
    • 79957438558 scopus 로고    scopus 로고
    • Shrink globally, act locally: Sparse bayesian regularization and prediction
    • Oxford University Press
    • Polson, N. G. and Scott, J. G. (2010). Shrink globally, act locally: Sparse Bayesian regularization and prediction. Bayesian Statistics 9. Oxford University Press.
    • (2010) Bayesian Statistics , pp. 9
    • Polson, N.G.1    Scott, J.G.2
  • 31
    • 0000940729 scopus 로고
    • Facilitating the Gibbs sampler: The gibbs stopper and the griddy-gibbs sampler
    • Ritter, C. and Tanner, M. A. (1992). Facilitating the Gibbs sampler: The Gibbs stopper and the griddy-Gibbs sampler. J. Amer. Statist. Assoc. 97, 861-868.
    • (1992) J. Amer. Statist. Assoc. , vol.97 , pp. 861-868
    • Ritter, C.1    Tanner, M.A.2
  • 32
    • 0000300851 scopus 로고
    • Proper bayes minimax estimators of the multivariate normal mean
    • Strawderman, W. E. (1971). Proper Bayes minimax estimators of the multivariate normal mean. Ann. Math. Statist. 42, 385-388.
    • (1971) Ann. Math. Statist. , vol.42 , pp. 385-388
    • Strawderman, W.E.1
  • 33
    • 0001287271 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. J. Roy. Statist. Soc. Ser. B 58, 267-288.
    • (1996) J. Roy. Statist. Soc. Ser. B , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 34
    • 0001224048 scopus 로고    scopus 로고
    • Sparse bayesian learning and the relevance vector machine
    • Tipping, M. E. (2001). Sparse Bayesian learning and the relevance vector machine. J. Machine Learning Research 1.
    • (2001) J. Machine Learning Research , pp. 1
    • Tipping, M.E.1
  • 35
    • 34548536572 scopus 로고    scopus 로고
    • Tuning parameter selectors for the smoothly clipped absolute deviation method
    • Wang, H., Li, R. and Tsai, C. L. (2007). Tuning parameter selectors for the smoothly clipped absolute deviation method. Biometrika 94, 553-568.
    • (2007) Biometrika , vol.94 , pp. 553-568
    • Wang, H.1    Li, R.2    Tsai, C.L.3
  • 36
    • 0039713775 scopus 로고
    • On scale mixtures of normal distributions
    • West, M. (1987). On scale mixtures of normal distributions. Biometrika 74, 646-648.
    • (1987) Biometrika , vol.74 , pp. 646-648
    • West, M.1
  • 37
    • 29144459062 scopus 로고    scopus 로고
    • Efficient empirical Bayes variable selection and estimation in linear models
    • Yuan, M. and Lin, Y. (2005). Efficient empirical Bayes variable selection and estimation in linear models. J. Amer. Statist. Assoc. 100, 1215-1225.
    • (2005) J. Amer. Statist. Assoc. , vol.100 , pp. 1215-1225
    • Yuan, M.1    Lin, Y.2
  • 38
  • 39
    • 33846114377 scopus 로고    scopus 로고
    • The adaptive lasso and its oracle properties
    • Zou, H. (2006). The adaptive lasso and its oracle properties. J. Amer. Statist. Assoc. 101, 1418-1429.
    • (2006) J. Amer. Statist. Assoc. , vol.101 , pp. 1418-1429
    • Zou, H.1
  • 40
    • 51049104549 scopus 로고    scopus 로고
    • One-step sparse estimates in nonconcave penalized likelihood models
    • Zou, H. and Li, R. (2008). One-step sparse estimates in nonconcave penalized likelihood models. Ann. Statist. 36, 1509-1533.
    • (2008) Ann. Statist. , vol.36 , pp. 1509-1533
    • Zou, H.1    Li, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.