One-step targeted minimum loss-based estimation based on universal least favorable one-dimensional submodels

DOI10.1515/ijb-2015-0054MaRDI QIDQ6632738

Susan Gruber, Mark Johannes van der Laan

Publication date: 5 November 2024

Published in: The International Journal of Biostatistics (Search for Journal in Brave)

zbMATH Keywords

MLEestimating equationinfluence curveone-step estimatorsuper-learningefficient influence curvecanonical gradienttargeted minimum loss-based estimation (TMLE)targeted maximum likelihood estimationasymptotic linear estimatorinfinite dimensional target parameterlocal least favorable submodelpathwise differentiable parameteruniversal canonical submodeluniversal least-favorable submodeluniversal score-specific submodel

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

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• An application of collaborative targeted maximum likelihood estimation in causal inference and genomics
• Targeted minimum loss based estimator that outperforms a given estimator

Related Items (3)

Nonparametric bootstrap inference for the targeted highly adaptive least absolute shrinkage and selection operator (LASSO) estimator ⋮ A generally efficient targeted minimum loss based estimator based on the highly adaptive Lasso ⋮ Efficient estimation of pathwise differentiable target parameters with the undersmoothed highly adaptive lasso

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