Discussion: One-step sparse estimates in nonconcave penalized likelihood models: Who cares if it is a white cat or a black cat?
Xiao-Li Meng
Source: Ann. Statist. Volume 36, Number 4 (2008), 1542-1552.
Primary Subjects: 62F99
Secondary Subjects: 62F15
Full-text: Access denied (no subscription detected)
We're sorry, but we are unable to provide you with the full text of this article because we are not able to identify you as a subscriber.
If you have a personal subscription to this journal, then please login. If you are already logged in, then you may need to update your profile to register your subscription. Read more about accessing full-text
This document is available for purchase at a cost of $15. Select the "buy article" button below to make a credit card purchase of this document through a secure payment site.
Links and Identifiers
Permanent link to this document: http://projecteuclid.org/euclid.aos/1216237289
Digital Object Identifier: doi:10.1214/07-AOS0316B
Mathematical Reviews number (MathSciNet):
MR2435445
References
[1] Abramovich, F., Sapatinas, T. and Silverman, B. W. (1998). Wavelet thresholding via a Bayesian approach. J. Roy. Statist. Soc. Ser. B 60 725–749.
Mathematical Reviews (MathSciNet):
MR1649547
Digital Object Identifier: doi:10.1111/1467-9868.00151
JSTOR: links.jstor.org
[2] Barndorff-Nielsen, O. (1987). Differential geometry and statistics: Some mathematical aspects. Indian J. Math. 29 335–350.
Mathematical Reviews (MathSciNet):
MR971645
[3] Barndorff-Nielsen, O. and Jupp, J. (1997). Yokes and symplectic structures. J. Statist. Plann. Inference 63 133–146.
Mathematical Reviews (MathSciNet):
MR1491574
Digital Object Identifier: doi:10.1016/S0378-3758(97)00006-2
[4] Blæsild, P. (1991). Yokes and tensors derived from yokes. Ann. Inst. Statist. Math. 43 95–113.
[5] Johnston, I. and Silverman, B. (2005). Empirical Bayes selection of wavelets thresholds. Ann. Statist. 33 1700–1753.
Mathematical Reviews (MathSciNet):
MR2166560
Digital Object Identifier: doi:10.1214/009053605000000345
Project Euclid: euclid.aos/1123250227
[6] Kong, A. snd McCullagh, P., Meng, X.-L. and Nicolae, D. (2007). Further explorations of likelihood theory for Monte Carlo integration. In Advances in Statistical Modeling and Inference: Essays in Honor of Kjell A Doksum (V. Nair, ed.) 563–592. World Scientific, Singapore.
Mathematical Reviews (MathSciNet):
MR2416134
[7] Kong, A. snd McCullagh, P., Meng, X.-L., Nicolae, D. and Tan, Z. (2003). A theory of statistical models for Monte Carlo integration (with discussion). J. Roy. Statist. Soc. Ser. B 65 585–618.
Mathematical Reviews (MathSciNet):
MR1998624
Digital Object Identifier: doi:10.1111/1467-9868.00404
JSTOR: links.jstor.org
[8] Lange, K., Hunter, D. and Yang, I. (2000). Optimization transfer using surrogate objective functions (with discussion). J. Comput. Graph. Statist. 9 1–59.
Mathematical Reviews (MathSciNet):
MR1819865
Digital Object Identifier: doi:10.2307/1390605
JSTOR: links.jstor.org
[9] Meng, X.-L. (1994). On the rate of convergence of the ECM algorithm. Ann. Statist. 22 326–339.
Mathematical Reviews (MathSciNet):
MR1272086
Digital Object Identifier: doi:10.1214/aos/1176325371
Project Euclid: euclid.aos/1176325371
[10] Meng, X.-L. (2000). Discussion of “Optimization transfer using surrogate objective functions” by K. Lange, D. Hunter and I. Yang. J. Comput. Graph. Statist. 9 35–43.
Mathematical Reviews (MathSciNet):
MR1819865
Digital Object Identifier: doi:10.2307/1390605
JSTOR: links.jstor.org
[11] Meng, X.-L. and Rubin, D. B. (1991). Using EM to obtain asymptotic variance-covariance matrices: The SEM algorithm. J. Amer. Statist. Assoc. 86 899–909.
[12] Meng, X.-L. and Rubin, D. B. (1994). On the global and componentwise rates of convergence of the EM algorithm. Linear Algebra Appl. 199 413–425.
Mathematical Reviews (MathSciNet):
MR1274429
Digital Object Identifier: doi:10.1016/0024-3795(94)90363-8
[13] Meng, X.-L. and van Dyk, D. A. (1997). The EM algorithm—an old folk song sung to a fast new tune (with discussion). J. Roy. Statist. Soc. Ser. B 59 511–567.
Mathematical Reviews (MathSciNet):
MR1452025
Digital Object Identifier: doi:10.1111/1467-9868.00082
JSTOR: links.jstor.org
[14] Meng, X.-L. and van Dyk, D. A. (1998). Fast EM-type implementations for mixed-effects models. J. Roy. Statist. Soc. Ser. B 60 559–578.
Mathematical Reviews (MathSciNet):
MR1625942
Digital Object Identifier: doi:10.1111/1467-9868.00140
JSTOR: links.jstor.org
[15] Silverman, B., Jones, M. C., Wilson, J. D. and Nychka, D. W. (1990). A smoothed EM approach to indirect estimation problems, with particular reference to stereology and emission tomography (with discussion). J. Roy. Statist. Soc. Ser. B 57 271–324.
The Annals of Statistics
