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A Starting Note: A Historical Perspective in Lasso

Year 2021, Volume 13, Issue 1, 1 - 3, 03.09.2021
https://doi.org/10.33818/ier.872633

Abstract

we provide history of lasso, and see new ventures and talk about key concept of debiased lasso. Lasso provided a good fit through sparse regression but did not deliver standard errors. The debiased lasso delivers.

References

  • Belloni, A. and D. Chen, and V. Chernozhukov, and C. Hansen (2012). Sparse models and methods for optimal instruments with an application to eminent domain. Econometrica, 80, 2369-2429.
  • Belloni, A. and V. Chernozhukov, and C. Hansen (2014). Inference on treatment effects after selection among high dimensional controls. Review of Economic Studies, 81, 608-650.
  • Callot, L. and M. Caner, and O. Onder, E. Ulasan (2021). A nodewise regression approach to estimating large portfolios. Journal of Business and Economic Statistics, Forthcoming.
  • Caner, M. (2009). Lasso-type GMM estimation. Econometric Theory, 25, 270-290.
  • Caner, M. and A.B. Kock (2018). Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative lasso. Journal of Econometrics, 203, 143-168.
  • Caner, M. and X. Han, and Y. Lee (2018). Adaptive elastic net GMM estimation with many invalid moment conditions: Simultaneous model and moment selection. Journal of Business and Economic Statistics, 36, 24-46.
  • Knight, K. and W. Fu (2000). Asymptotics for lasso-type estimators. Annals of Statistics, 28, 1356-1378.
  • Knight, K. (2008). Shrinkage estimation for nearly singular designs. Econometric Theory, 24, 323-337.
  • Leeb, H. and B. Potscher (2003). The finite sample distribution of post-model selection estimators and uniform versus nonuniform approximations. Econometric Theory 19, 100-142.
  • Leeb, H. and B. Potscher (2005). Model selection and inference: facts and fiction. Econometric Theory, 21, 21-59.
  • Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society Series B, 58,267-288.
  • Van de Geer, S. and P. Buhlmann, and Y. Ritov, and R. Dezeure (2014). On asymptotically optimal confidence regions and tests for high dimensional models. Annals of Statistics, 42, 1166-1202.
  • Zou, H. (2006). The adaptive lasso and its oracle properties. Journal of the American Statistical Association, 101, 1418-1429.

Year 2021, Volume 13, Issue 1, 1 - 3, 03.09.2021
https://doi.org/10.33818/ier.872633

Abstract

References

  • Belloni, A. and D. Chen, and V. Chernozhukov, and C. Hansen (2012). Sparse models and methods for optimal instruments with an application to eminent domain. Econometrica, 80, 2369-2429.
  • Belloni, A. and V. Chernozhukov, and C. Hansen (2014). Inference on treatment effects after selection among high dimensional controls. Review of Economic Studies, 81, 608-650.
  • Callot, L. and M. Caner, and O. Onder, E. Ulasan (2021). A nodewise regression approach to estimating large portfolios. Journal of Business and Economic Statistics, Forthcoming.
  • Caner, M. (2009). Lasso-type GMM estimation. Econometric Theory, 25, 270-290.
  • Caner, M. and A.B. Kock (2018). Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative lasso. Journal of Econometrics, 203, 143-168.
  • Caner, M. and X. Han, and Y. Lee (2018). Adaptive elastic net GMM estimation with many invalid moment conditions: Simultaneous model and moment selection. Journal of Business and Economic Statistics, 36, 24-46.
  • Knight, K. and W. Fu (2000). Asymptotics for lasso-type estimators. Annals of Statistics, 28, 1356-1378.
  • Knight, K. (2008). Shrinkage estimation for nearly singular designs. Econometric Theory, 24, 323-337.
  • Leeb, H. and B. Potscher (2003). The finite sample distribution of post-model selection estimators and uniform versus nonuniform approximations. Econometric Theory 19, 100-142.
  • Leeb, H. and B. Potscher (2005). Model selection and inference: facts and fiction. Econometric Theory, 21, 21-59.
  • Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society Series B, 58,267-288.
  • Van de Geer, S. and P. Buhlmann, and Y. Ritov, and R. Dezeure (2014). On asymptotically optimal confidence regions and tests for high dimensional models. Annals of Statistics, 42, 1166-1202.
  • Zou, H. (2006). The adaptive lasso and its oracle properties. Journal of the American Statistical Association, 101, 1418-1429.

Details

Primary Language English
Subjects Economics
Journal Section Articles
Authors

Mehmet CANER (Primary Author)
North Carolina State University
United States

Publication Date September 3, 2021
Published in Issue Year 2021, Volume 13, Issue 1

Cite

Bibtex @review { ier872633, journal = {International Econometric Review}, issn = {1308-8793}, eissn = {1308-8815}, address = {Şairler Sokak, No:32/C, Gaziosmanpaşa, Ankara}, publisher = {Econometric Research Association}, year = {2021}, volume = {13}, pages = {1 - 3}, doi = {10.33818/ier.872633}, title = {A Starting Note: A Historical Perspective in Lasso}, key = {cite}, author = {Caner, Mehmet} }
APA Caner, M. (2021). A Starting Note: A Historical Perspective in Lasso . International Econometric Review , 13 (1) , 1-3 . DOI: 10.33818/ier.872633
MLA Caner, M. "A Starting Note: A Historical Perspective in Lasso" . International Econometric Review 13 (2021 ): 1-3 <https://dergipark.org.tr/en/pub/ier/issue/64789/872633>
Chicago Caner, M. "A Starting Note: A Historical Perspective in Lasso". International Econometric Review 13 (2021 ): 1-3
RIS TY - JOUR T1 - A Starting Note: A Historical Perspective in Lasso AU - Mehmet Caner Y1 - 2021 PY - 2021 N1 - doi: 10.33818/ier.872633 DO - 10.33818/ier.872633 T2 - International Econometric Review JF - Journal JO - JOR SP - 1 EP - 3 VL - 13 IS - 1 SN - 1308-8793-1308-8815 M3 - doi: 10.33818/ier.872633 UR - https://doi.org/10.33818/ier.872633 Y2 - 2021 ER -
EndNote %0 International Econometric Review A Starting Note: A Historical Perspective in Lasso %A Mehmet Caner %T A Starting Note: A Historical Perspective in Lasso %D 2021 %J International Econometric Review %P 1308-8793-1308-8815 %V 13 %N 1 %R doi: 10.33818/ier.872633 %U 10.33818/ier.872633
ISNAD Caner, Mehmet . "A Starting Note: A Historical Perspective in Lasso". International Econometric Review 13 / 1 (September 2021): 1-3 . https://doi.org/10.33818/ier.872633
AMA Caner M. A Starting Note: A Historical Perspective in Lasso. IER. 2021; 13(1): 1-3.
Vancouver Caner M. A Starting Note: A Historical Perspective in Lasso. International Econometric Review. 2021; 13(1): 1-3.
IEEE M. Caner , "A Starting Note: A Historical Perspective in Lasso", International Econometric Review, vol. 13, no. 1, pp. 1-3, Sep. 2021, doi:10.33818/ier.872633