A. Bowcock, W. Shannon, F. Du, J. Duncan, K. Cao et al., Insights into psoriasis and other inflammatory diseases from large-scale gene expression studies, Human Molecular Genetics, vol.10, issue.17, pp.10-1793, 2001.
DOI : 10.1093/hmg/10.17.1793

URL : https://academic.oup.com/hmg/article-pdf/10/17/1793/9813517/101793.pdf

J. Campos, D. F. Hendry, and H. M. Krolzig, Consistent Model Selection by an Automatic Gets Approach*, Oxford Bulletin of Economics and Statistics, vol.78, issue.s1, pp.803-819, 2003.
DOI : 10.1016/0005-1098(78)90005-5

J. A. Doornik, Autometrics The Methodology and Practice of Econometrics, pp.88-122, 2009.

B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, Least angle regression, The Annals of Statistics, pp.407-499, 2004.

J. Fan and R. Li, Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties, Journal of the American Statistical Association, vol.96, issue.456, pp.1348-1360, 2001.
DOI : 10.1198/016214501753382273

J. H. Friedman, T. Hastie, and R. Tibshirani, Regularized Paths for Generalized Linear Models via Coordinate Descent, Journal of Statistical Software, vol.33, issue.1, 2010.
DOI : 10.18637/jss.v033.i01

URL : https://doi.org/10.18637/jss.v033.i01

D. Harvey, S. Leybourne, and P. Newbold, Testing the equality of prediction mean squared errors, International Journal of Forecasting, vol.13, issue.2, pp.281-291, 1997.
DOI : 10.1016/S0169-2070(96)00719-4

D. F. Hendry, H. K. Krolzig, S. J. Hoover, and . Perez, Improving on 'Data mining reconsidered' by K.D. Hoover and S.J. Perez, The Econometrics Journal, vol.2, issue.2, pp.202-219, 1999.
DOI : 10.1111/1368-423X.00027

D. F. Hendry and H. Krolzig, Resolving three 'intractable' problems using a Gets approach, 2004.

D. F. Hendry and B. Nielsen, Econometric Modeling: A Likelihood Approach, 2007.

M. Fariñas, Histological Stratification of Thick and Thin Plaque Psoriasis Explores Molecular Phenotypes with Clinical Implications, PLoS ONE, vol.10, issue.7, p.132454, 2015.

H. Krolzig and D. F. Hendry, Computer automation of general-to-specific model selection procedures, Journal of Economic Dynamics and Control, vol.25, issue.6-7, pp.831-866, 2001.
DOI : 10.1016/S0165-1889(00)00058-0

M. C. Medeiros and E. F. Mendes, <mml:math altimg="si53.gif" display="inline" overflow="scroll" xmlns:xocs="http://www.elsevier.com/xml/xocs/dtd" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.elsevier.com/xml/ja/dtd" xmlns:ja="http://www.elsevier.com/xml/ja/dtd" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:tb="http://www.elsevier.com/xml/common/table/dtd" xmlns:sb="http://www.elsevier.com/xml/common/struct-bib/dtd" xmlns:ce="http://www.elsevier.com/xml/common/dtd" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:cals="http://www.elsevier.com/xml/common/cals/dtd" xmlns:sa="http://www.elsevier.com/xml/common/struct-aff/dtd"><mml:msub><mml:mrow><mml:mi>???</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:math>-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors, Journal of Econometrics, vol.191, issue.1, pp.255-271, 2016.
DOI : 10.1016/j.jeconom.2015.10.011

N. Meinshausen and B. Yu, Lasso-type recovery of sparse representations for high dimensional data. The Annals of Statistics, pp.246-270, 2009.

T. Perez-amaral, G. M. Gallo, and H. White, A Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)*, Oxford Bulletin of Economics and Statistics, vol.64, issue.s1, 2003.
DOI : 10.1111/1468-0262.00152

M. Suárez-fariñas, K. Li, J. Fuentes-duculan, K. Hayden, C. Brodmerkel et al., Expanding the Psoriasis Disease Profile: Interrogation of the Skin and Serum of Patients with Moderate-to-Severe Psoriasis, Journal of Investigative Dermatology, vol.132, issue.11, pp.132-2552, 2012.
DOI : 10.1038/jid.2012.184

S. Tian, J. G. Krueger, K. Li, A. Jabbari, and C. Brodmerkel, Meta-Analysis Derived (MAD) Transcriptome of Psoriasis Defines the ???Core??? Pathogenesis of Disease, PLoS ONE, vol.7, issue.9, p.44274, 2012.
DOI : 10.1371/journal.pone.0044274.s008

S. Tian and M. Suárez-fariñas, Multi-TGDR: A Regularization Method for Multi-Class Classification in Microarray Experiments, PLoS ONE, vol.23, issue.11, p.78302, 2013.
DOI : 10.1371/journal.pone.0078302.t007

R. Tibshirani, Regression shrinkage and selection via the Lasso, Journal of the Royal Statistical Society. Series BMethodological), vol.58, issue.1, pp.267-288, 1996.
DOI : 10.1111/j.1467-9868.2011.00771.x

R. Tibshirani, Regression shrinkage and selection via the lasso: a retrospective, JRSSB retrospective read paper, pp.273-282, 2011.
DOI : 10.1214/009053607000000802

H. Wang, G. Li, and C. Tsai, Regression coefficient and autoregressive order shrinkage and selection via the lasso, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.67, issue.1, pp.63-78, 2007.
DOI : 10.1007/978-1-4757-3261-0

URL : http://hansheng.gsm.pku.edu.cn/pdf/2007/RA-Lasso (main).pdf

H. White, Approximate nonlinear forecasting methods, 2006.
DOI : 10.1016/s1574-0706(05)01009-8

A. Granger and . Timmermann, Handbook of Economic Forecasting, pp.459-512

Y. Zhang, R. Li, and C. Tsai, Regularization Parameter Selections via Generalized Information Criterion, Journal of the American Statistical Association, vol.105, issue.489, pp.312-323, 2010.
DOI : 10.1198/jasa.2009.tm08013

URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2911045/pdf

P. Zhao and B. Yu, On model consistency of lasso, Journal of Machine Learning Research, vol.7, pp.2541-2563, 2006.

H. Zou, The Adaptive Lasso and Its Oracle Properties, Journal of the American Statistical Association, vol.101, issue.476, pp.1418-1429, 2006.
DOI : 10.1198/016214506000000735

URL : http://cbio.ensmp.fr/~jvert/svn/bibli/local/Zou2006adaptive.pdf

H. Zou and T. Hastie, Regularization and variable selection via the elastic net, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.5, issue.2, pp.301-320, 2005.
DOI : 10.1073/pnas.201162998

H. Zou, T. Hastie, and R. Tibshirani, On the ???degrees of freedom??? of the lasso, The Annals of Statistics, vol.35, issue.5, pp.2173-2192, 2007.
DOI : 10.1214/009053607000000127