References

Akaike, H. 1974. “A New Look at the Statistical Model Identification.” IEEE Transactions on Automatic Control AC-19: 716–23.

Benjamini, Y., and Y. Hochberg. 1995. “Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing.” Journal of the Royal Statistical Society, Ser. B 57: 289–300.

Berk, R., L. Brown, A. Buja, K. Zhang, and L. Zhao. 2013. “Valid Post-Selection Inference.” The Annals of Statistics 41: 802–37.

Breheny, P., and J. Huang. 2011. “Coordinate Descent Algorithms for Nonconvex Penalized Regression, with Applications to Biological Feature Selection.” The Annals of Applied Statistics 5: 232–53.

Breiman, L. 1984. Classification and Regression Trees. Chapman & Hall.

———. 1994. “Bagging Predictors.” Technical Report 421. Department of Statistics, University of California, Berkeley.

———. 1995. “Better Subset Regression Using the Nonnegative Garrote.” Technometrics 37: 373–84.

———. 1996. “Bagging Predictors.” Machine Learning 24: 123–40.

Buja, A., and K. Zhang. 2015. “PoSI: Valid Post-Selection Inference for Linear LS Regression.” R Package.

Bühlmann, P., M. Kalisch, and M. H. Maathuis. 2010. “Variable Selection in High-Dimensional Linear Models: Partially Faithful Distributions and the PC-Simple Algorithm.” Biometrika 97: 261–78.

Claeskens, Gerda, and Nils Lid Hjort. 2003. “The Focused Information Criterion.” Journal of the American Statistical Association 98: 900–945.

Cowell, F. A. 2011. Measuring Inequality. Third Edition. Oxford: Oxford University Press.

Donoho, David L., and Iain M. Johnstone. 1995. “Adapting to Unknown Smoothness via Wavelet Shrinkage.” Journal of the American Statistical Association 90: 1200–1224.

Efron, B. 1978. “The Geometry of Exponential Families.” The Annals of Statistics 6: 362–76.

———. 1979. “Bootstrap Methods: Another Look at the Jacknife.” Annst 7: 1–26.

———. 1986a. “How Biased is the Apparent Error Rate of a Prediction Rule?” Journal of the American Statistical Association 81 (394). Taylor & Francis: 461–70.

———. 1986b. “How Biased Is the Apparent Error Rate of a Prediction Rule?” Journal of the American Statistical Association 81 (394): 461–70. http://www.jstor.org/stable/2289236.

———. 2004. “The Estimation of Prediction Error.” Journal of the American Statistical Association 99 (467). Taylor & Francis: 619–32.

———. 2014. “Estimation and Accuracy After Model Selection.” Journal of the American Statistical Association 109: 991–1007.

Efron, B., and T. Hastie. 2016. Computer Age Statistical Inference: Algorithms, Evidence, and Data Science. Cambridge University Press.

Efron, B., and R. Tibshirani. 1996. “Using Specially Designed Exponential Families for Density Estimation.” Annals of Statististics 24: 2431–61.

Efron, B., T. Hastie, I. Johnstone, and R. Tibshirani. 2004. “Least Angle Regression (with Discussion).” Annals of Statistics 32: 407–99.

Efron, B., and C. Stein. 1981. “The Jackknife Estimate of Variance.” Annals of Statististics 9: 586–96.

Fan, J., and R. Li. 2001. “Variable Selection via Nonconcave Penalized Likelihood and Its Oracle Properties.” Journal of the American Statistical Association 96 (456). Taylor & Francis: 1348–60.

Fan, J., and J. Lv. 2008. “Sure Independence Screening for Ultrahigh Dimensional Feature Space.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 70 (5). Wiley Online Library: 849–911.

Fernholz, L. 2001. “On Multivariate Higher Order von Mises Expansions.” Metrika 53: 123–40.

Fisher, R. A. 1915. “Frequency Distribution of the Values of the Correlation Coeficient in Samples from an Indefinitely Large Population.” Biometrika 10: 507–21.

———. 1921. “On the ‘Probable Error’ of a Coefficient of Correlation Deduced from a Small Sample.” Metron 1: 3–32.

Foster, D., and R Stine. 2004. “Variable Selection in Data Mining: Building a Predictive Model for Bankruptcy.” Journal of the American Statistical Association 99: 303–13.

Golub, Todd R, Donna K Slonim, Pablo Tamayo, Christine Huard, Michelle Gaasenbeek, Jill P Mesirov, Hilary Coller, et al. 1999. “Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring.” Science 286 (5439). American Association for the Advancement of Science: 531–37.

Goodnight, J. H. 1979. “A Tutorial on the SWEEP Operator.” The American Statistician 33: 149–58.

Gordon, Gavin J, Roderick V Jensen, Li-Li Hsiao, Steven R Gullans, Joshua E Blumenstock, Sridhar Ramaswamy, William G Richards, David J Sugarbaker, and Raphael Bueno. 2002. “Translation of Microarray Data into Clinically Relevant Cancer Diagnostic Tests Using Gene Expression Ratios in Lung Cancer and Mesothelioma.” Cancer Research 62 (17). AACR: 4963–7.

G’Sell, M. G., S. Wager, A. Chouldechova, and R. Tibshirani. 2016. “Sequential Selection Procedures and False Discovery Rate Control.” Journal of the Royal Statististical Society, B 78: 423–44.

Hastie, T., J. Taylor, R. Tibshirani, and G. Walther. 2007. “Forward Stagewise Regression and the Monotone Lasso.” Electronic Journal of Statistics 1: 1–29.

Hastie, Trevor, Tibshirani Robert, and Jerome Friedman. 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Second Edition. Springer Series in Statistics. Springer.

Hoerl, A. E., and R. Kennard. 1970. “Ridge Regression: Biased Estimation for Nonorthogonal Problems.” Technometrics 12: 55–67.

Huber, P. J., and E. M. Ronchetti. 2009. Robust Statistics. Second Edition. Wiley Series in Probability and Statistics. John Wiley & Sons.

James, G., D. Witten, T. Hastie, and R. Tibshirani. 2013. An Introduction to Statistical Learning: With Applications in R. New York: Springer.

James, W., and C. Stein. 1961. “Estimation with Quadratic Loss.” In Proc. 4th Berkeley Symposium on Mathematical Statistics and Probability, Vol. I, 361–79. University of California Press.

Kim, Y., S. Kwon, and H. Choi. 2012. Journal of Machine Learning Research 13: 1037–57.

Lee, J. D., D. L. Sun, Y. Sun, and J. E. Taylor. 2016. “Exact Post-Selection Inference, with Application to the Lasso.” The Annals of Statistics 44: 907–27.

Lee, J., and J. Taylor. 2014. “Exact Post Model Selection Inference for Marginal Screening.” Advances in Neural Information Processing Systems 27: 136–44.

Leeb, H., and B. M. Pötscher. 2008. “Sparse Estimators and the Oracle Property, or the Return of Hodges’ Estimator.” Journal of Econometrics 142: 201–11.

Lin, D., D. P. Foster, and L. H. Ungar. 2011. “VIF Regression: A Fast Regression Algorithm for Large Data.” Journal of the American Statistical Association 106: 232–47.

Mallows, C. L. 1973. “Some Comments on \(C_p\).” Technometrics 15: 661–75.

McQuarrie, A.D.R., and C.L. Tsai. 1998. Regression and Time Series Model Selection. World Scientific.

Meinshausen, N. 2007. “Relaxed Lasso.” Computational Statistics and Data Analysis 52: 374–93.

Quenouille, Maurice H. 1956. “Notes on Bias in Estimation.” Biometrika 43: 353–60.

Reid, S., R. Tibshirani, and J. Friedman. 2016. “A Study of Error Variance Eestimation in Lasso Regression.” Statistica Sinica 26: 35–67.

Schwarz, G. 1978. “Estimating the Dimension of a Model.” Annst 6: 461–64.

Shannon, C. E. 1948a. “A Mathematical Theory of Communication.” Bell System Technical Journal 27: 379–423.

———. 1948b. “A Mathematical Theory of Communication.” Bell System Technical Journal 27: 623–66.

Shao, J. 1997. “An Asymptotic Theory for Linear Model Selection.” Statistica Sinica 7: 221–42.

Singh, Dinesh, Phillip G Febbo, Kenneth Ross, Donald G Jackson, Judith Manola, Christine Ladd, Pablo Tamayo, et al. 2002. “Gene Expression Correlates of Clinical Prostate Cancer Behavior.” Cancer Cell 1 (2). Elsevier: 203–9.

Spirtes, P., C. Glymour, and R. Scheines. 2000. Causation, Prediction, and Search. MIT Press.

Stein, C. M. 1981. “Estimation of the Mean of a Multivariate Normal Distribution.” The Annals of Statistics 9: 1135–51.

Sutton, C. D. 2005. “11 - Classification and Regression Trees, Bagging, and Boosting.” In Data Mining and Data Visualization, edited by C.R. Rao, E.J. Wegman, and J.L. Solka, 24:303–29. Handbook of Statistics. Elsevier.

Tibshirani, R. 1996. “Regression Shrinkage and Selection via the Lasso.” Jrssb 58: 267–88.

Tibshirani, R. J. 2015. “A General Framework for Fast Stagewise Algorithms.” Journal of Machine Learning Research 16: 2543–88.

Tukey, John W. 1958. “Bias and Confidence in Not Quite Large Samples (Abstract).” The Annals of Mathematical Statistics 29: 614.

United Nations Children’s Fund. 1998. “The State of the World’s Children 1998: Focus on Nutrition.” UNICEF, New York, USA.

———. 2012. “The State of the World’s Children 2012: Children in an Urban World.” UNICEF, New York, USA.

Vapnik, V. 1996. The Nature of Statistical Learning Theory. New York: Springer.

Victora, C. G., L. Adair, C. Fall, P. C. Hallal, R. Martorell, L. Richter, and H. S. Sachdev. 2008. “Maternal and Child Undernutrition: Consequences for Adult Health and Human Capital.” Lancet 371 (9609). Elsevier: 340.

Wager, S., T. Hastie, and B. Efron. 2014. “Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife.” Journal of Machine Learning Research 15: 1625–51.

Xiong, S. 2010. “Some Notes on the Nonnegative Garrote.” Technometrics 52 (3): 349–61.

Yang, Y. 2005. “Can the Strengths of AIC and BIC Be Shared? A Conflict Between Model Indentification and Regression Estimation.” Biometrika 92: 937–50.

Yuan, M., and Yi Lin. 2007. “On the Non-Negative Garrotte Estimator.” Journal of the Royal Statististical Sociaty, Series B 69: 143–61.

Zhang, C.-H. 2010. “Nearly Unbiased Variable Selection Under Minimax Concave Penalty.” The Annals of Statistics 38: 894–942.

Zhang, D., A. Khalili, and M. Asgharian. 2022. “Post-Model-Selection Inference in Linear Regression Models: An Integrated Review.” Statistics Surveys 16: 86–136.

Zhang, T. 2009. “On the Consistency of Feature Selection Using Greedy Least Squares Regression.” Journal of Machine Learning Research 10: 555–68.

Zhou, J., D. P. Foster, R. A. Stine, and L. H. Ungar. 2006. “Streamwise Feature Selection.” Journal of Machine Learning Research 7: 1861–85.

Zou, H. 2006. “The Adaptive Lasso and Its Oracle Properties.” Journal of the American Statistical Association 101: 1418–29.

Zou, H., and T. Hastie. 2005. “Regularization and Variable Selection via the Elastic Net.” Journal of the Royal Statistical Society: Series B 67 (2). Wiley Online Library: 301–20.