REFERENCES
- Barut, E., Fan, J., and Verhasselt, A. (2015), “Conditional Sure Independence Screening,” Journal of the American Statistical Association, to appear, DOI: 10.1080/01621459.2015.1092974.
- Belloni, A., Chernozhukov, V., and Hansen, C. (2014a), “Inference on Treatment Effects After Selection among High-Dimensional Controls,” Review of Economic Studies, 81, 608–650.
- Belloni, A., Chernozhukov, V., and Kato, K. (2014b), “Uniform Post-Selection Inference for Least Absolute Deviation Regression and Other Z-Estimation Problems,” Biometrika, 102, 77–94.
- Buja, A., Berk, R., Brown, L.D., George, E., Pitkin, E., Traskin, M., Zhao, L., and Zhang, K. (in press), “Models as Approximations—A Conspiracy of Random Regressors and Model Deviations Against Classical Inference in Regression,” Statistical Science.
- Efron, B., and Tibshirani, R.J. (1993), An Introduction to the Bootstrap (Monographs on Statistics & Applied Probability), Boca Raton, FL: Chapman & Hall/CRC.
- Hastie, T., Tibshirani, R., and Friedman, J. (2009), The Elements of Statistical Learning, New York: Springer.
- Javanmard, A., and Montanari, A. (2015), “Confidence Intervals and Hypothesis Testing for High-Dimensional Regression,” Journal of Machine Learning Research, 15, 2869–2909.
- Leeb, H., and Pötscher, B.M. (2006), “Performance Limits for Estimators of the Risk or Distribution of Shrinkage-Type Estimators, and Some General Lower Risk-Bound Results,” Econometric Theory, 22, 69–97.
- ——— (2014), “Testing in the Presence of Nuisance Parameters: Some Comments on Tests Post-Model-Selection and Random Critical Values,” arXiv:1209.4543.