VARIABLE SELECTION FOR REGRESSION MODELS

作者: Lynn Kuo , Bani Mallick

DOI:

关键词:

摘要: … variable selection? One may argue that the Bayesian paradigm already offers an alternative to variable selection, … Although we do not discuss the truncated normal component here, we …

参考文章(24)
Merlise Clyde, Giovanni Parmigiani, Orthogonalizations and Prior Distributions for Orthogonalized Model Mixing Modelling and Prediction Honoring Seymour Geisser. pp. 206- 227 ,(1996) , 10.1007/978-1-4612-2414-3_13
Peter McCullagh, John Ashworth Nelder, Generalized Linear Models ,(1983)
Adrian Raftery, David Madigan, Jennifer Hoeting, MODEL SELECTION AND ACCOUNTING FOR MODEL UNCERTAINTY IN LINEAR REGRESSION MODELS ,(2007)
Bradley P. Carlin, Siddhartha Chib, Bayesian Model Choice Via Markov Chain Monte Carlo Methods Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 57, pp. 473- 484 ,(1995) , 10.1111/J.2517-6161.1995.TB02042.X
Jennifer Hoeting, Adrian E. Raftery, David Madigan, A method for simultaneous variable selection and outlier identification in linear regression Computational Statistics & Data Analysis. ,vol. 22, pp. 251- 270 ,(1996) , 10.1016/0167-9473(95)00053-4
Edward I. George, Robert E. McCulloch, Variable Selection via Gibbs Sampling Journal of the American Statistical Association. ,vol. 88, pp. 881- 889 ,(1993) , 10.1080/01621459.1993.10476353
Stuart Geman, Donald Geman, Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. PAMI-6, pp. 721- 741 ,(1984) , 10.1109/TPAMI.1984.4767596
Jose Ferreira de Carvalho, N. R. Draper, H. Smith, Applied regression analysis 2nd ed. Journal of the American Statistical Association. ,vol. 76, pp. 1012- ,(1981) , 10.2307/2287608
Merlise Clyde, Heather Desimone, Giovanni Parmigiani, Prediction via Orthogonalized Model Mixing Journal of the American Statistical Association. ,vol. 91, pp. 1197- 1208 ,(1996) , 10.1080/01621459.1996.10476989