The thesis introduces the Local Covariance Measure test for conditional local independence, the Debiased Outcome-adapted Propensity Estimator for efficient covariate adjustment, and the Aalen Covariance Measure for assumption-lean Aalen regression.
Uniform approximation in classical weak convergence theory
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
A common statistical task lies in showing asymptotic normality of certain statistics. In many of these situations, classical textbook results on weak convergence theory suffice for the problem at hand. However, there are quite some scenarios where stronger results are needed in order to establish an asymptotic normal approximation uniformly over a family of probability measures. In this note we collect some results in this direction. We restrict ourselves to weak convergence in $\mathbb R^d$ with continuous limit measures.
fields
stat.ME 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Model-free Methods for Event History Analysis and Efficient Adjustment (PhD Thesis)
The thesis introduces the Local Covariance Measure test for conditional local independence, the Debiased Outcome-adapted Propensity Estimator for efficient covariate adjustment, and the Aalen Covariance Measure for assumption-lean Aalen regression.