References

The entries below collect the external books, articles, and lecture notes used alongside van der Vaart’s Asymptotic Statistics.

Bailie, James. 2021. Stat213 Lecture Notes. Course lecture notes, Harvard University. https://jameshbailie.github.io/files/papers/2021-06-16-Asymptotic-statistics.pdf.
Bickel, Peter J., Chris A. J. Klaassen, Ya’acov Ritov, and Jon A. Wellner. 1993. Efficient and Adaptive Estimation for Semiparametric Models. Johns Hopkins Series in the Mathematical Sciences. Johns Hopkins University Press. https://link.springer.com/book/9780387984735.
Chernozhukov, Victor, Denis Chetverikov, Mert Demirer, et al. 2018. “Double/Debiased Machine Learning for Treatment and Structural Parameters.” The Econometrics Journal 21 (1): C1–68. https://doi.org/10.1111/ectj.12097.
DasGupta, Anirban. 2008. Asymptotic Theory of Statistics and Probability. Springer Texts in Statistics. Springer. https://doi.org/10.1007/978-0-387-75971-5.
Fisher, Aaron, and Edward H. Kennedy. 2021. “Visually Communicating and Teaching Intuition for Influence Functions.” The American Statistician 75 (2): 162–72. https://doi.org/10.1080/00031305.2020.1717620.
Gill, Richard D., and Søren Johansen. 1990. “A Survey of Product-Integration with a View Toward Application in Survival Analysis.” The Annals of Statistics 18 (4): 1501–55. https://doi.org/10.1214/aos/1176347865.
Jiang, Jiming. 2022. Large Sample Techniques for Statistics. 2nd ed. Springer Texts in Statistics. Springer. https://doi.org/10.1007/978-3-030-91695-4.
Kennedy, Edward H. 2016. “Semiparametric Theory and Empirical Processes in Causal Inference.” In Statistical Causal Inferences and Their Applications in Public Health Research, edited by Hua He, Pan Wu, and Ding-Geng Chen. ICSA Book Series in Statistics. Springer International Publishing. https://doi.org/10.1007/978-3-319-41259-7_8.
Kennedy, Edward H. 2022. Semiparametric Doubly Robust Targeted Double Machine Learning: A Review. https://doi.org/10.48550/arXiv.2203.06469.
Kosorok, Michael R. 2008. Introduction to Empirical Processes and Semiparametric Inference. Springer Series in Statistics. Springer. https://doi.org/10.1007/978-0-387-74978-5.
Le Cam, Lucien, and Grace Lo Yang. 2000. Asymptotics in Statistics: Some Basic Concepts. 2nd ed. Springer Series in Statistics. Springer. https://doi.org/10.1007/978-1-4612-1166-2.
Murphy, Susan A., and Aad W. van der Vaart. 1996. “Likelihood Inference in the Errors-in-Variables Model.” Journal of Multivariate Analysis 59 (1): 81–108. https://doi.org/10.1006/jmva.1996.0055.
Pollard, David. 2002. A User’s Guide to Measure Theoretic Probability. Cambridge Series in Statistical and Probabilistic Mathematics 8. Cambridge University Press. https://doi.org/10.1017/CBO9780511811555.
Robins, James M., Andrea Rotnitzky, and Lue Ping Zhao. 1994. “Estimation of Regression Coefficients When Some Regressors Are Not Always Observed.” Journal of the American Statistical Association 89 (427): 846–66. https://doi.org/10.1080/01621459.1994.10476818.
Sen, Bodhisattva. 2022. A Gentle Introduction to Empirical Process Theory and Applications. Lecture notes, Department of Statistics, Columbia University. https://sites.stat.columbia.edu/bodhi/Talks/Emp-Proc-Lecture-Notes.pdf.
Tsiatis, Anastasios A. 2006. Semiparametric Theory and Missing Data. Springer Series in Statistics. Springer. https://doi.org/10.1007/0-387-37345-4.
Tsybakov, Alexandre B. 2009. Introduction to Nonparametric Estimation. Springer Series in Statistics. Springer. https://doi.org/10.1007/b13794.
Vaart, Aad W. van der. 1991. “On Differentiable Functionals.” The Annals of Statistics 19 (1): 178–204. https://doi.org/10.1214/aos/1176347976.
Vaart, Aad W. van der. 1996. “Efficient Maximum Likelihood Estimation in Semiparametric Mixture Models.” The Annals of Statistics 24 (2): 862–78. https://doi.org/10.1214/aos/1032894470.
van der Vaart, Aad W., and Jon A. Wellner. 1996. Weak Convergence and Empirical Processes: With Applications to Statistics. Springer Series in Statistics. Springer. https://doi.org/10.1007/978-1-4757-2545-2.