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Citations for "Addendum: Regularization and variable selection via the elastic net"

by Hui Zou & Trevor Hastie

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  1. Caiya Zhang & Yanbiao Xiang, 2016. "On the oracle property of adaptive group Lasso in high-dimensional linear models," Statistical Papers, Springer, vol. 57(1), pages 249-265, March.
  2. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, 09.
  3. Chudik, Alexander & Kapetanios, George & Pesaran, M. Hashem, 2016. "Big data analytics: a new perspective," Globalization and Monetary Policy Institute Working Paper 268, Federal Reserve Bank of Dallas.
  4. Plakandaras, Vasilios & Gupta, Rangan & Papadimitriou, Theophilos & Gogas, Periklis, 2014. "Forecasting the U.S. Real House Price Index," DUTH Research Papers in Economics 10-2014, Democritus University of Thrace, Department of Economics.
  5. Hongjin He & Xingju Cai & Deren Han, 2015. "A fast splitting method tailored for Dantzig selector," Computational Optimization and Applications, Springer, vol. 62(2), pages 347-372, November.
  6. Jiahan Li & Ilias Tsiakas & Wei Wang, 2014. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Working Paper Series 05_14, The Rimini Centre for Economic Analysis.
  7. Mandal, B.N. & Ma, Jun, 2016. "l1 regularized multiplicative iterative path algorithm for non-negative generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 289-299.
  8. Hsu, David, 2015. "Identifying key variables and interactions in statistical models of building energy consumption using regularization," Energy, Elsevier, vol. 83(C), pages 144-155.
  9. Wang, Siyang & Cui, Hengjian, 2015. "A new test for part of high dimensional regression coefficients," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 187-203.
  10. Schumacher, Christian, 2009. "Factor forecasting using international targeted predictors: the case of German GDP," Discussion Paper Series 1: Economic Studies 2009,10, Deutsche Bundesbank, Research Centre.
  11. Adam Nowak & Patrick Smith, 2015. "Textual Analysis in Real Estate," Working Papers 15-34, Department of Economics, West Virginia University.
  12. Peter Bühlmann & Jacopo Mandozzi, 2014. "High-dimensional variable screening and bias in subsequent inference, with an empirical comparison," Computational Statistics, Springer, vol. 29(3), pages 407-430, June.
  13. Huang, Qiming & Zhu, Yu, 2016. "Model-free sure screening via maximum correlation," Journal of Multivariate Analysis, Elsevier, vol. 148(C), pages 89-106.
  14. Alec Smith & B. Douglas Bernheim & Colin F. Camerer & Antonio Rangel, 2014. "Neural Activity Reveals Preferences without Choices," American Economic Journal: Microeconomics, American Economic Association, vol. 6(2), pages 1-36, May.
  15. Kim, Hyun Hak & Swanson, Norman R., 2014. "Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence," Journal of Econometrics, Elsevier, vol. 178(P2), pages 352-367.
  16. Cai, Jia & Xiang, Dao-Hong, 2016. "Statistical consistency of coefficient-based conditional quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 149(C), pages 1-12.
  17. Boriss Siliverstovs, 2015. "Dissecting the Purchasing Managers’ Index: Are all relevant components included? Are all included components relevant?," KOF Working papers 15-376, KOF Swiss Economic Institute, ETH Zurich.
  18. Fan, Jianqing & Liao, Yuan, 2012. "Endogeneity in ultrahigh dimension," MPRA Paper 38698, University Library of Munich, Germany.
  19. Daye, Z. John & Jeng, X. Jessie, 2009. "Shrinkage and model selection with correlated variables via weighted fusion," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1284-1298, February.
  20. Ma, Shaohui & Fildes, Robert & Huang, Tao, 2016. "Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra- and inter-category promotional information," European Journal of Operational Research, Elsevier, vol. 249(1), pages 245-257.
  21. Eickmeier, Sandra & Ng, Tim, 2011. "Forecasting national activity using lots of international predictors: An application to New Zealand," International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511, April.
  22. Tutz, Gerhard & Binder, Harald, 2007. "Boosting ridge regression," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6044-6059, August.
  23. Matthias Weber & Martin Schumacher & Harald Binder, 2014. "Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs," Tinbergen Institute Discussion Papers 14-089/I, Tinbergen Institute.
  24. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," Journal of Econometrics, Elsevier, vol. 177(2), pages 357-373.
  25. Seema Narayan & Russell Smyth, 2015. "The Financial Econometrics of Price Discovery and Predictability," Monash Economics Working Papers 06-15, Monash University, Department of Economics.
  26. Xue-Jun Ma & Jing-Xiao Zhang, 2016. "A new variable selection approach for varying coefficient models," Metrika- International Journal for Theoretical and Applied Statistics, Springer, vol. 79(1), pages 59-72, January.
  27. Patric Müller & Sara Geer, 2016. "Censored linear model in high dimensions," TEST- An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 75-92, March.
  28. Victor Chernozhukov & Christian Hansen & Yuan Liao, 2015. "A lava attack on the recovery of sums of dense and sparse signals," CeMMAP working papers CWP56/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  29. Abdallah Mkhadri & Mohamed Ouhourane, 2015. "A group VISA algorithm for variable selection," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 41-60, March.
  30. Xia, X.H. & Huang, G.T. & Chen, G.Q. & Zhang, Bo & Chen, Z.M. & Yang, Q., 2011. "Energy security, efficiency and carbon emission of Chinese industry," Energy Policy, Elsevier, vol. 39(6), pages 3520-3528, June.
  31. repec:prg:jnlpep:v:preprint:id:581:p:1-20 is not listed on IDEAS
  32. Charles Bouveyron & Camille Brunet-Saumard, 2014. "Discriminative variable selection for clustering with the sparse Fisher-EM algorithm," Computational Statistics, Springer, vol. 29(3), pages 489-513, June.
  33. Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
  34. Beckmann, Joscha & Schüssler, Rainer, 2016. "Forecasting exchange rates under parameter and model uncertainty," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 267-288.
  35. Hu, Qinqin & Zeng, Peng & Lin, Lu, 2015. "The dual and degrees of freedom of linearly constrained generalized lasso," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 13-26.
  36. Wang, Mingqiu & Song, Lixin & Wang, Xiaoguang, 2010. "Bridge estimation for generalized linear models with a diverging number of parameters," Statistics & Probability Letters, Elsevier, vol. 80(21-22), pages 1584-1596, November.
  37. Roberts, S. & Nowak, G., 2014. "Stabilizing the lasso against cross-validation variability," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 198-211.
  38. Nott, David J. & Leng, Chenlei, 2010. "Bayesian projection approaches to variable selection in generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3227-3241, December.
  39. Wang, Tao & Zhu, Lixing, 2011. "Consistent tuning parameter selection in high dimensional sparse linear regression," Journal of Multivariate Analysis, Elsevier, vol. 102(7), pages 1141-1151, August.
  40. Mielniczuk, Jan & Teisseyre, Paweł, 2014. "Using random subspace method for prediction and variable importance assessment in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 725-742.
  41. Daniel Ambach & Carsten Croonenbroeck, 2016. "Space-time short- to medium-term wind speed forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 5-20, March.
  42. W. Braun, 2015. "Visualization of evidence in regression with the QR decomposition," Computational Statistics, Springer, vol. 30(4), pages 907-927, December.
  43. Ziel, Florian, 2016. "Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR–ARCH type processes," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 773-793.
  44. Latouche, Pierre & Mattei, Pierre-Alexandre & Bouveyron, Charles & Chiquet, Julien, 2016. "Combining a relaxed EM algorithm with Occam’s razor for Bayesian variable selection in high-dimensional regression," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 177-190.
  45. Menon, Aditya Krishna & Cai, Chen & Wang, Weihong & Wen, Tao & Chen, Fang, 2015. "Fine-grained OD estimation with automated zoning and sparsity regularisation," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 150-172.
  46. Wolfgang Karl Härdle & Dedy Dwi Prastyo, 2013. "Default Risk Calculation based on Predictor Selection for the Southeast Asian Industry," SFB 649 Discussion Papers SFB649DP2013-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  47. Michoel, Tom, 2016. "Natural coordinate descent algorithm for L1-penalised regression in generalised linear models," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 60-70.
  48. Sandra Stankiewicz, 2015. "Forecasting Euro Area Macroeconomic Variables with Bayesian Adaptive Elastic Net," Working Paper Series of the Department of Economics, University of Konstanz 2015-12, Department of Economics, University of Konstanz.
  49. Korobilis, Dimitris, 2013. "Hierarchical shrinkage priors for dynamic regressions with many predictors," International Journal of Forecasting, Elsevier, vol. 29(1), pages 43-59.
  50. Philip Kostov & Thankom Arun & Samuel Annim, 2014. "Financial Services to the Unbanked: the case of the Mzansi intervention in South Africa," Contemporary Economics, University of Finance and Management in Warsaw, vol. 8(2), June.
  51. Yoonseok Lee & Mehmet Caner & Xu Han, 2015. "Adaptive Elastic Net GMM Estimation with Many Invalid Moment Conditions: Simultaneous Model and Moment Selection," Center for Policy Research Working Papers 177, Center for Policy Research, Maxwell School, Syracuse University.
  52. Enis Kayış & Taghi Khaniyev & Jaap Suermondt & Karl Sylvester, 2015. "A robust estimation model for surgery durations with temporal, operational, and surgery team effects," Health Care Management Science, Springer, vol. 18(3), pages 222-233, September.
  53. Boriss Siliverstovs, 2015. "Short-term forecasting with mixed-frequency data: A MIDASSO approach," KOF Working papers 15-375, KOF Swiss Economic Institute, ETH Zurich.
  54. Hyun Hak Kim & Norman Swanson, 2013. "Mining Big Data Using Parsimonious Factor and Shrinkage Methods," Departmental Working Papers 201316, Rutgers University, Department of Economics.
  55. Shi, Minghui & Dunson, David B., 2011. "Bayesian variable selection via particle stochastic search," Statistics & Probability Letters, Elsevier, vol. 81(2), pages 283-291, February.
  56. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
  57. Gefang, Deborah, 2014. "Bayesian doubly adaptive elastic-net Lasso for VAR shrinkage," International Journal of Forecasting, Elsevier, vol. 30(1), pages 1-11.
  58. Yao, Weixin & Wang, Qin, 2013. "Robust variable selection through MAVE," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 42-49.
  59. David Hendry & Felix Pretis & Lea Schneider & Jason E. Smerdon, 2016. "Detecting Volcanic Eruptions in Temperature Reconstructions by Designed Break-Indicator Saturation," Economics Series Working Papers 780, University of Oxford, Department of Economics.
  60. Jan P.A.M. Jacobs & Pieter W. Otter & Ard H.J. den Reijer, 2011. "Information, data dimension and factor structure," CAMA Working Papers 2011-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  61. Lee, Youngjo & Oh, Hee-Seok, 2014. "A new sparse variable selection via random-effect model," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 89-99.
  62. Wang, Xiaoming & Park, Taesung & Carriere, K.C., 2010. "Variable selection via combined penalization for high-dimensional data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2230-2243, October.
  63. Changrong Yan & Dixin Zhang, 2013. "Sparse dimension reduction for survival data," Computational Statistics, Springer, vol. 28(4), pages 1835-1852, August.
  64. Luo, Ruiyan & Qi, Xin, 2015. "Sparse wavelet regression with multiple predictive curves," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 33-49.
  65. Oliver J. Rutz & Michael Trusov & Randolph E. Bucklin, 2011. "Modeling Indirect Effects of Paid Search Advertising: Which Keywords Lead to More Future Visits?," Marketing Science, INFORMS, vol. 30(4), pages 646-665, July.
  66. Zhou, Jingke & Zhu, Lixing, 2016. "Principal minimax support vector machine for sufficient dimension reduction with contaminated data," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 33-48.
  67. Xue-Jun Ma & Jing-Xiao Zhang, 2016. "A new variable selection approach for varying coefficient models," Metrika- International Journal for Theoretical and Applied Statistics, Springer, vol. 79(1), pages 59-72, January.
  68. Baragatti, M. & Pommeret, D., 2012. "A study of variable selection using g-prior distribution with ridge parameter," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1920-1934.
  69. Ueki, Masao & Kawasaki, Yoshinori, 2013. "Multiple choice from competing regression models under multicollinearity based on standardized update," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 31-41.
  70. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Exchange Rates under Model and Parameter Uncertainty," CQE Working Papers 3214, Center for Quantitative Economics (CQE), University of Muenster.
  71. repec:dau:papers:123456789/10079 is not listed on IDEAS
  72. Daeju Kim & Shuichi Kawano & Yoshiyuki Ninomiya, 2014. "Adaptive basis expansion via $$\ell _1$$ ℓ 1 trend filtering," Computational Statistics, Springer, vol. 29(5), pages 1005-1023, October.
  73. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
  74. Chakraborty, Sounak, 2009. "Bayesian binary kernel probit model for microarray based cancer classification and gene selection," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4198-4209, October.
  75. Ard Reijer, 2013. "Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets," Empirical Economics, Springer, vol. 44(2), pages 435-453, April.
  76. Peter Bühlmann, 2013. "Causal statistical inference in high dimensions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 357-370, June.
  77. Tian, Tian Siva & James, Gareth M., 2013. "Interpretable dimension reduction for classifying functional data," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 282-296.
  78. Rohart, Florian & San Cristobal, Magali & Laurent, Béatrice, 2014. "Selection of fixed effects in high dimensional linear mixed models using a multicycle ECM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 209-222.
  79. Julius Stakenas, 2012. "Generating short-term forecasts of the Lithuanian GDP using factor models," Bank of Lithuania Working Paper Series 13, Bank of Lithuania.
  80. Lykou, Anastasia & Whittaker, Joe, 2010. "Sparse CCA using a Lasso with positivity constraints," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3144-3157, December.
  81. Shutes, Karl & Adcock, Chris, 2013. "Regularized Skew-Normal Regression," MPRA Paper 52217, University Library of Munich, Germany, revised 11 Dec 2013.
  82. Shen, Haipeng & Huang, Jianhua Z., 2008. "Sparse principal component analysis via regularized low rank matrix approximation," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1015-1034, July.
  83. McKay Curtis, S. & Banerjee, Sayantan & Ghosal, Subhashis, 2014. "Fast Bayesian model assessment for nonparametric additive regression," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 347-358.
  84. Mingkun Chen & Evelyne Vigneau, 2016. "Supervised clustering of variables," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(1), pages 85-101, March.
  85. Blommaert, A. & Hens, N. & Beutels, Ph., 2014. "Data mining for longitudinal data under multicollinearity and time dependence using penalized generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 667-680.
  86. Jiang, Liewen & Bondell, Howard D. & Wang, Huixia Judy, 2014. "Interquantile shrinkage and variable selection in quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 208-219.
  87. Yang, Hu & Yi, Danhui, 2015. "Studies of the adaptive network-constrained linear regression and its application," Computational Statistics & Data Analysis, Elsevier, vol. 92(C), pages 40-52.
  88. Shutes, Karl & Adcock, Chris, 2013. "Regularized Extended Skew-Normal Regression," MPRA Paper 58445, University Library of Munich, Germany, revised 09 Sep 2014.
  89. McCann, Lauren & Welsch, Roy E., 2007. "Robust variable selection using least angle regression and elemental set sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 249-257, September.
  90. Feng Li & Lu Lin & Yuxia Su, 2013. "Variable selection and parameter estimation for partially linear models via Dantzig selector," Metrika- International Journal for Theoretical and Applied Statistics, Springer, vol. 76(2), pages 225-238, February.
  91. Lian, Heng, 2012. "Shrinkage estimation for identification of linear components in additive models," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 225-231.
  92. Lin, Huazhen & Peng, Heng, 2013. "Smoothed rank correlation of the linear transformation regression model," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 615-630.
  93. Malefaki, Valia, 2015. "On Flexible Linear Factor Stochastic Volatility Models," MPRA Paper 62216, University Library of Munich, Germany.
  94. Kawano, Shuichi & Fujisawa, Hironori & Takada, Toyoyuki & Shiroishi, Toshihiko, 2015. "Sparse principal component regression with adaptive loading," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 192-203.
  95. Wang, Tao & Zhu, Lixing, 2013. "Sparse sufficient dimension reduction using optimal scoring," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 223-232.
  96. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.
  97. Nott, David J., 2008. "Predictive performance of Dirichlet process shrinkage methods in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3658-3669, March.
  98. Stephanie Möst & Wolfgang Pößnecker & Gerhard Tutz, 2016. "Variable selection for discrete competing risks models," Quality & Quantity- International Journal of Methodology, Springer, vol. 50(4), pages 1589-1610, July.
  99. Gerda Claeskens, 2012. "Focused estimation and model averaging with penalization methods: an overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(3), pages 272-287, 08.
  100. Hidetoshi Matsui & Toshihiro Misumi, 2015. "Variable selection for varying-coefficient models with the sparse regularization," Computational Statistics, Springer, vol. 30(1), pages 43-55, March.
  101. Ruggieri, Eric & Lawrence, Charles E., 2012. "On efficient calculations for Bayesian variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1319-1332.
  102. Friedman, Jerome H., 2012. "Fast sparse regression and classification," International Journal of Forecasting, Elsevier, vol. 28(3), pages 722-738.
  103. Mai, Qing & Zou, Hui, 2015. "Sparse semiparametric discriminant analysis," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 175-188.
  104. Marcelo C. Medeiros & Eduardo F. Mendes, 2015. "l1-Regularization of High-Dimensional Time-Series Models with Flexible Innovations," Textos para discussão 636, Department of Economics PUC-Rio (Brazil).
  105. Zhou, Ding-Xuan, 2013. "On grouping effect of elastic net," Statistics & Probability Letters, Elsevier, vol. 83(9), pages 2108-2112.
  106. Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
  107. Huang, Zhensheng & Pang, Zhen & Lin, Bingqing & Shao, Quanxi, 2014. "Model structure selection in single-index-coefficient regression models," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 159-175.
  108. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
  109. Wang, Qin & Yin, Xiangrong, 2008. "A nonlinear multi-dimensional variable selection method for high dimensional data: Sparse MAVE," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4512-4520, May.
  110. K. Kampa & S. Mehta & C. Chou & W. Chaovalitwongse & T. Grabowski, 2014. "Sparse optimization in feature selection: application in neuroimaging," Journal of Global Optimization- An International Journal Dealing with Theoretical and Computational Aspects of Seeking Global Optima and Their Applications in Science, Management and Engineering, Springer, vol. 59(2), pages 439-457, July.
  111. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87.
  112. Xing, Xin & Hu, Jinjin & Yang, Yaning, 2014. "Robust minimum variance portfolio with L-infinity constraints," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 107-117.
  113. Chalise, Prabhakar & Fridley, Brooke L., 2012. "Comparison of penalty functions for sparse canonical correlation analysis," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 245-254.
  114. Michael Schomaker, 2012. "Shrinkage averaging estimation," Statistical Papers, Springer, vol. 53(4), pages 1015-1034, November.
  115. Mehmet Caner & Anders Bredahl Kock, 2013. "Oracle Inequalities for Convex Loss Functions with Non-Linear Targets," CREATES Research Papers 2013-51, Department of Economics and Business Economics, Aarhus University.
  116. Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," CESifo Working Paper Series 5824, CESifo Group Munich.
  117. Korzeń, M. & Jaroszewicz, S. & Klęsk, P., 2013. "Logistic regression with weight grouping priors," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 281-298.
  118. Brendan P. W. Ames & Mingyi Hong, 2016. "Alternating direction method of multipliers for penalized zero-variance discriminant analysis," Computational Optimization and Applications, Springer, vol. 64(3), pages 725-754, July.
  119. van Wieringen, Wessel N. & Kun, David & Hampel, Regina & Boulesteix, Anne-Laure, 2009. "Survival prediction using gene expression data: A review and comparison," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1590-1603, March.
  120. Shuichi Kawano, 2014. "Selection of tuning parameters in bridge regression models via Bayesian information criterion," Statistical Papers, Springer, vol. 55(4), pages 1207-1223, November.
  121. A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," Cambridge Working Papers in Economics 1611, Faculty of Economics, University of Cambridge.
  122. Chakraborty, Sounak & Guo, Ruixin, 2011. "A Bayesian hybrid Huberized support vector machine and its applications in high-dimensional medical data," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1342-1356, March.
  123. Florian Ziel, 2015. "Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR-ARCH type processes," Papers 1502.06557, arXiv.org, revised Dec 2015.
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