Regression coefficient and autoregressive order shrinkage and selection via the lasso
暂无分享,去创建一个
[1] D. Cochrane,et al. Application of Least Squares Regression to Relationships Containing Auto-Correlated Error Terms , 1949 .
[2] Gwilym M. Jenkins,et al. Time series analysis, forecasting and control , 1971 .
[3] P. Young,et al. Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.
[4] H. Akaike,et al. Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .
[5] Andrew Harvey,et al. The econometric analysis of time series , 1991 .
[6] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[7] W. D. Ray,et al. The Econometric Analysis of Time Series. , 1981 .
[8] Ruey S. Tsay. Regression Models with Time Series Errors , 1984 .
[9] R. Ramanathan,et al. Introductory Econometrics With Applications , 1989 .
[10] Clifford M. Hurvich,et al. The impact of model selection on inference in linear regression , 1990 .
[11] Richard A. Davis,et al. Time Series: Theory and Methods , 2013 .
[12] ByoungSeon Choi,et al. Arma Model Identification , 1992 .
[13] Richard A. Davis,et al. Time Series: Theory and Methods (2Nd Edn) , 1993 .
[14] James D. Hamilton. Time Series Analysis , 1994 .
[15] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[16] L. Breiman. Heuristics of instability and stabilization in model selection , 1996 .
[17] C. Gouriéroux. ARCH Models and Financial Applications , 1997 .
[18] J. Shao. AN ASYMPTOTIC THEORY FOR LINEAR MODEL SELECTION , 1997 .
[19] Wenjiang J. Fu. Penalized Regressions: The Bridge versus the Lasso , 1998 .
[20] A. McQuarrie,et al. Regression and Time Series Model Selection , 1998 .
[21] Wenjiang J. Fu,et al. Asymptotics for lasso-type estimators , 2000 .
[22] Jianqing Fan,et al. Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties , 2001 .
[23] Jianqing Fan,et al. Variable Selection for Cox's proportional Hazards Model and Frailty Model , 2002 .
[24] H. Zou,et al. Regression Shrinkage and Selection via the Elastic Net , with Applications to Microarrays , 2003 .
[25] Jianqing Fan,et al. Nonconcave penalized likelihood with a diverging number of parameters , 2004, math/0406466.
[26] R. Tibshirani,et al. Least angle regression , 2004, math/0406456.
[27] Chih-Ling Tsai,et al. A Joint Regression Variable and Autoregressive Order Selection Criterion , 2004 .
[28] R. Tibshirani,et al. On the “degrees of freedom” of the lasso , 2007, 0712.0881.
[29] H. Zou,et al. Regularization and variable selection via the elastic net , 2005 .
[30] G. Wahba,et al. A NOTE ON THE LASSO AND RELATED PROCEDURES IN MODEL SELECTION , 2006 .
[31] Benedikt M. Potscher,et al. On the distribution of the adaptive LASSO estimator , 2008, 0801.4627.
[32] Benedikt M. Pötscher. Confidence Sets Based on Sparse Estimators Are Necessarily Large , 2007 .
[33] S. Pandey,et al. What Are Degrees of Freedom , 2008 .
[34] Hansheng Wang,et al. Computational Statistics and Data Analysis a Note on Adaptive Group Lasso , 2022 .
[35] Shurong Zheng,et al. Selection of components and degrees of smoothing via lasso in high dimensional nonparametric additive models , 2008, Comput. Stat. Data Anal..
[36] Nan-Jung Hsu,et al. Subset selection for vector autoregressive processes using Lasso , 2008, Comput. Stat. Data Anal..
[37] Ding Yi,et al. Time series analysis and its application , 2008, 2008 Chinese Control and Decision Conference.