Fetching the paper…
Reading the bibliography…
While model selection is a well-studied topic in parametric and nonparametric regression or density estimation, selection of possibly high-dimensional nuisance parameters in semiparametric problems is far less developed.
Rosenbaum, P. R. and Rubin, D. B. (1983), “The Central Role of the Propensity Score in Observational Studies for Causal Effects,” Biometrika
1983
Earlier work this paper cites.
Robins, J. M., Li, L., Mukherjee, R., Tchetgen Tchetgen, E., and van der Vaart, A. (2017), “Minimax estimation of a functional on a structured high-dimensional model,” Ann. Statist
1987
Earlier work this paper cites.
Newey, W. K. (1990), “Semiparametric efficiency bounds,” Journal of applied econometrics
1990
Earlier work this paper cites.
Bickel, P. J., Klaassen, C. A., Bickel, P. J., Ritov, Y., Klaassen, J., Wellner, J. A., and Ritov, Y. (1993), Efficient and adaptive estimation for semiparametric models
1993
Earlier work this paper cites.
Robins, J. M., Rotnitzky, A., and Zhao, L. P. (1994), “Estimation of Regression Coefficients When Some Regressors are not Always Observed,” Journal of the American Statistical Association
1994
Earlier work this paper cites.
Connors, A., Speroff, T., Dawson, N., Thomas, C., Harrell, F., Wagner, D., Desbiens, N., Goldman, L., Wu, A., Califf, R., Fulkerson, W., Vidaillet, H., Broste, S., Bellamy, P., Lynn, J., and Knaus, W. (1996), “The effectiveness of right heart catheterization in the initial care of critically ill patients,” JAMA - Journal of the American Medical Association
1996
Earlier work this paper cites.
Tibshirani, R. (1996), “Regression Shrinkage and Selection via the Lasso,” Journal of the Royal Statistical Society. Series B (Methodological)
1996
Earlier work this paper cites.
Rotnitzky, A., Robins, J. M., and Scharfstein, D. O. (1998), “Semiparametric Regression for Repeated Outcomes with Nonignorable Nonresponse,” Journal of the American Statistical Association
1998
Earlier work this paper cites.
Scharfstein, D. O., Rotnitzky, A., and Robins, J. M. (1999), “Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models,” Journal of the American Statistical Association
1999
Earlier work this paper cites.
Giné, E., Latała, R., and Zinn, J. (2000), “Exponential and Moment Inequalities for U U -Statistics,” in High Dimensional Probability II
2000
Earlier work this paper cites.
Breiman, L. (2001), “Random Forests,” Machine Learning
2001
Earlier work this paper cites.
Friedman, J. H. (2001), “Greedy function approximation: a gradient boosting machine,” Annals of statistics
2001
Earlier work this paper cites.
Hirano, K. and Imbens, G. W. (2001), “Estimation of Causal Effects using Propensity Score Weighting: An Application to Data on Right Heart Catheterization,” Health Services and Outcomes Research Methodology
2001
Earlier work this paper cites.
Robins, J. and Rotnitzky, A. G. (2001), “Comment on the Bickel and Kwon article, ’Inference for semiparametric models: Some questions and an answer’,” Statistica Sinica
2001
Earlier work this paper cites.
van der Laan, M. J. and Robins, J. M. (2003), Unified Methods for Censored Longitudinal Data and Causality
2003
Earlier work this paper cites.
Bang, H. and Robins, J. M. (2005), “Doubly Robust Estimation in Missing Data and Causal Inference Models,” Biometrics
2005
Earlier work this paper cites.
Tan, Z. (2006), “A Distributional Approach for Causal Inference Using Propensity Scores,” Journal of the American Statistical Association
2006
Cited alongside, same era.
van der Vaart, A. W., Dudoit, S., and van der Laan, M. J. (2006), “Oracle inequalities for multi-fold cross validation,” Statistics & Decisions
2006
Cited alongside, same era.
Robins, J., Sued, M., Lei-Gomez, Q., and Rotnitzky, A. (2007), “Double-robust and efficient methods for estimating the causal effects of a binary treatment,”
2007
Cited alongside, same era.
Robins, J. M., Li, L., Tchetgen Tchetgen, E., and van der Vaart, A. (2008), “Higher order influence functions and minimax estimation of nonlinear functionals,” IMS Collections: Probability and Statistics: Essays in Honor of David A. Freedman
2008
Cited alongside, same era.
Chan, K. C. G. and Yam, S. C. P. (2014), “Oracle, Multiple Robust and Multipurpose Calibration in a Missing Response Problem,” Statist. Sci
2014
Later among the works it cites.
Vermeulen, K. and Vansteelandt, S. (2015), “Bias-Reduced Doubly Robust Estimation,” Journal of the American Statistical Association
2015
Later among the works it cites.
— (2016), “Data-Adaptive Bias-Reduced Doubly Robust Estimation,” The International Journal of Biostatistics
2016
Later among the works it cites.
Chen, S. and Haziza, D. (2017), “Multiply robust imputation procedures for the treatment of item nonresponse in surveys,” Biometrika
2017
Later among the works it cites.
Duan, X. and Yin, G. (2017), “Ensemble Approaches to Estimating the Population Mean with Missing Response,” Scandinavian Journal of Statistics
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2009
Cited alongside, same era.
Friedman, J., Hastie, T., and Tibshirani, R. (2010), “Regularization paths for generalized linear models via coordinate descent,” Journal of statistical software
2010
Cited alongside, same era.
— (2010), “Bounded, efficient and doubly robust estimation with inverse weighting,” Biometrika
2010
Cited alongside, same era.
Tchetgen Tchetgen, E. J., Robins, J., and Rotnitzky, A. G. (2010), “On doubly robust estimation in a semiparametric odds ratio model,” Biometrika
2010
Cited alongside, same era.
van der Laan, M. J. and Gruber, S. (2010), “Collaborative double robust targeted maximum likelihood estimation,” The international journal of biostatistics
2010
Cited alongside, same era.
Zheng, W. and van der Laan, M. J. (2010), “Asymptotic theory for cross-validated targeted maximum likelihood estimation,” Technical Report
2010
Cited alongside, same era.
2011
Cited alongside, same era.
van der Laan, M. J. and Rose, S. (2011), Targeted learning: causal inference for observational and experimental data
2011
Cited alongside, same era.
Wright, M. N. and Ziegler, A. (2017), “ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R,” Journal of Statistical Software
2017
Later among the works it cites.
2017
Later among the works it cites.
Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., Newey, W., and Robins, J. (2018), “Double/debiased machine learning for treatment and structural parameters,” The Econometrics Journal
2018
Later among the works it cites.
2018
Later among the works it cites.
— (2018), Targeted Learning in Data Science
2018
Later among the works it cites.
Greenwell, B., Boehmke, B., Cunningham, J., and Developers, G. (2019), gbm: Generalized Boosted Regression Models
2019
Closest in time.
Benkeser, D., Cai, W., and van der Laan, M. J. (2020), “A Nonparametric Super-Efficient Estimator of the Average Treatment Effect,” Statistical Science
2020
Closest in time.
Li, W., Gu, Y., and Liu, L. (2020), “Demystifying a class of multiply robust estimators,” Biometrika
2020
Closest in time.
Polley, E., LeDell, E., Kennedy, C., and van der Laan, M. (2021), SuperLearner: Super Learner Prediction
2021
Closest in time.
Rotnitzky, A., Smucler, E., and Robins, J. M. (2021), “Characterization of parameters with a mixed bias property,” Biometrika
2021
Closest in time.