Higher Order Tangent Spaces and Influence Functions

By A. van der Vaart. 2014

60 citations recorded by the source corpus.

We review higher order tangent spaces and influence functions and their use to construct minimax efficient estimators for parameters in highdimensional semiparametric models.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/967d8d8b7dd1be2c02880990a5c8ca1fafba3ebb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Edward H. Kennedy
2. Zongming Ma
3. Dylan S. Small
4. Matthew McHugh
5. E. T. Tchetgen Tchetgen
6. Lingling Li
7. Rajarshi Mukherjee
8. Robins

In Statistics and Probability

1. Edward H. Kennedy
2. E. T. Tchetgen Tchetgen
3. A. van der Vaart
4. Dylan S. Small
5. Lingling Li
6. Zongming Ma
7. Matthew McHugh
8. Iv'an D'iaz

Citations in the corpus

• Stacked Generalization: An Introduction to Super Learning (2017, unknown): “Specifically, there is no theory to support the resulting estimator is asymptotically linear (i.e., consistent and asymptotically normal), which is required to obtain, for example, centered confidence intervals with nominal coverage properties [33, 36].”
• Non‐parametric methods for doubly robust estimation of continuous treatment effects (2015, methodology): “This paper integrates semiparametric (doubly robust) causal inference with non-parametric function estimation and machine learning, helping to bridge the ‘huge gap between classical semiparametric models and the model in which nothing is assumed’ (van der Vaart, 2014).”
• MINIMAX ESTIMATION OF A FUNCTIONAL ON A STRUCTURED (2016, methodology): “The mathematical contributions of the paper are to provide a heuristic for constructing minimax estimators in semiparametric models, and to apply this to a concrete model, which is a template for a number of other models (see [23, 33]).”
• Global sensitivity analysis for repeated measures studies with informative drop‐out: A semi‐parametric approach (2018, background): “24 of van der Vaart (2000) implies that condition (a) holds provided it can be established that”