References
- Begun, J., Hall, W., Huang, W., and Wellner, J. (1983), “Information and Asymptotic Efficiency in Parametric-Nonparametric Models,” The Annals of Statistics, 11, 432–452.
- Bickel, P., Klaassen, C., Ritov, Y., and Wellner, J. (1997), Efficient and Adaptive Estimation for Semiparametric Models, New York: Springer.
- Bickel, P., and Ritov, Y. (1988), “Estimating Integrated Squared Density Derivatives: Sharp Best Order of Convergence Estimates,” Sankhyā: The Indian Journal of Statistics, Series A, 50, 381–393.
- Chambaz, A., and van der Laan, M. J. (2014), “Inference in Targeted Group-Sequential Covariate-Adjusted Randomized Clinical Trials,” Scandinavian Journal of Statistics, 41, 104–140.
- Chamberlain, G. (1987), “Asymptotic Efficiency in Estimation with Conditional Moment Restrictions,” Journal of Econometrics, 34, 305–334.
- Chen, X. (2007), “Large Sample Sieve Estimation of Semi-Nonparametric Models,” Handbook of Econometrics, 6, 5549–5632.
- Fornberg, B. (1988), “Generation of Finite Difference Formulas on Arbitrarily Spaced Grids,” Mathematics of Computation, 51, 699–706.
- Frangakis, C., Qian, T., Wu, Z., and Díaz, I. (2015), “Deductive Derivation and Turing-Computerization of Semiparametric Efficient Estimation” (with discussion), Biometrics, 71, 867–874.
- Geskus, R., and Groeneboom, P. (1999), “Asymptotically Optimal Estimation of Smooth Functionals for Interval Censoring, case 2,” The Annals of Statistics, 27, 627–674.
- Gilbert, P. B., Yu, X., and Rotnitzky, A. (2014), “Optimal Auxiliary-Covariate-Based Two-Phase Sampling Design for Semiparametric Efficient Estimation of a Mean or Mean Difference, with Application to Clinical Trials,” Statistics in Medicine, 33, 901–917.
- Hájek, J. (1970), “A Characterization of Limiting Distributions of Regular Estimates,” Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete, 14, 323–330.
- ——— (1972), “Local Asymptotic Minimax and Admissibility in Estimation,” in Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics and Probability (Vol. 1), Berkeley, CA: University of California Press, pp. 175–194.
- Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., and Stahel, W. A. (2011), Robust Statistics: The Approach Based on Influence Functions (Vol. 196), New York: Wiley.
- Ichimura, H., and Newey, W. (2015), “The Influence Function of Semiparametric Estimators,” arXiv preprint arXiv:1508.01378.
- Kiefer, J., and Wolfowitz, J. (1956), “Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters,” The Annals of Mathematical Statistics, 27, 887–906.
- Koshevnik, Y., and Levit, B. (1977), “On a Non-Parametric Analogue of the Information Matrix,” Theory of Probability & Its Applications, 21, 738–753.
- Le Cam, L. (1972), “Limits of Experiments,” in Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics and Probability (Vol. 1), Berkeley, CA: University of California Press, pp. 245–261.
- Luedtke, A., Carone, M., and van der Laan, M. J. (2015), “A Discussion of Deductive Derivation and Turing-Computerization of Semiparametric Efficient Estimation” by Frangakis et al.” Biometrics, 71, 875–879.
- Maathuis, M. H., and Wellner, J. A. (2008), “Inconsistency of the MLE for the Joint Distribution of Interval-Censored Survival Times and Continuous Marks,” Scandinavian Journal of Statistics, 35, 83–103.
- Newey, W. (1994), “The Asymptotic Variance of Semiparametric Estimators,” Econometrica, 62, 1349–1382.
- ——— (1997), “Convergence Rates and Asymptotic Normality for Series Estimators,” Journal of Econometrics, 79, 147–168.
- Pfanzagl, J. (1982), Contributions to a General Asymptotic Statistical Theory, New York: Springer.
- Quale, C. M., van der Laan, M. J., and Robins, J. M. (2006), “Locally Efficient Estimation with Bivariate Right-Censored Data,” Journal of the American Statistical Association, 101, 1076–1084.
- Robins, J. M. (1986), “A New Approach to Causal Inference in Mortality Studies with a Sustained Exposure Period Application to Control of the Healthy Worker Survivor Effect,” Mathematical Modelling, 7, 1393–1512.
- Shen, X. (1997), “On Methods of Sieves and Penalization,” The Annals of Statistics, 25, 2555–2591.
- Stein, C. (1956), “Efficient Nonparametric Testing and Estimation,” in Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability (Vol. 1), Berkeley, CA: University of California Press, pp. 187–195.
- Tsiatis, A. (2007), Semiparametric Theory and Missing Data, New York: Springer Science & Business Media.
- van der Laan, M. J. (1996), “Efficient Estimation in the Bivariate Censoring Model and Repairing NPMLE,” The Annals of Statistics, 24, 596–627.
- van der Laan, M. J., and Robins, J. M. (2003), Unified Methods for Censored Longitudinal Data and Causality, New York: Springer.
- van der Laan, M. J., and Rose, S. (2011), Targeted Learning: Causal Inference for Observational and Experimental Data, New York: Springer.
- van der Laan, M. J., and Rose, S. (2018), Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies, New York: Springer.
- van der Laan, M. J., and Rubin, D. (2006), “Targeted Maximum Likelihood Learning,” The International Journal of Biostatistics, 2.
- van der Vaart, A. (1991), “On Differentiable Functionals,” The Annals of Statistics, 19, 178–204.
- van der Vaart, A. (2014), “Higher Order Tangent Spaces and Influence Functions,” Statistical Science, 29, 679–686.
- Wong, W., and Severini, T. (1991), “On Maximum Likelihood Estimation in Infinite Dimensional Parameter Spaces,” The Annals of Statistics, 19, 603–632.