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.