Handbook of Quantile Regression
High-dimensional quantile regression
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, Chapter
Belloni, A; Chernozhukov, V; Kato, K
January 1, 2017
High-dimensional models arise from the need for practitioners to improve the accuracy and validity of current models and to handle the increasing availability of data. Large models can arise from using a very flexible specification with many parameters when the functional form is unknown or from having a data-rich environment with many variables that need to be incorporated into the model.
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Belloni, A., Chernozhukov, V., & Kato, K. (2017). High-dimensional quantile regression. In Handbook of Quantile Regression (pp. 253–272). https://doi.org/10.1201/9781315120256
Belloni, A., V. Chernozhukov, and K. Kato. “High-dimensional quantile regression.” In Handbook of Quantile Regression, 253–72, 2017. https://doi.org/10.1201/9781315120256.
Belloni A, Chernozhukov V, Kato K. High-dimensional quantile regression. In: Handbook of Quantile Regression. 2017. p. 253–72.
Belloni, A., et al. “High-dimensional quantile regression.” Handbook of Quantile Regression, 2017, pp. 253–72. Scopus, doi:10.1201/9781315120256.
Belloni A, Chernozhukov V, Kato K. High-dimensional quantile regression. Handbook of Quantile Regression. 2017. p. 253–272.