9 citations · 18 across the 16 of their papers we have counts for
6 papers · 1 filter
Toward a Semiparametric Efficiency Theory under Equality Constraints in Nested Markov Models
Razieh Nabi, Anna Guo, Lin Liu
Probabilistic models of Directed Acyclic Graphs (DAGs) with latent variables impose equality constraints on the observed data distribution beyond ordinary conditional independencie…
Stabilized Higher-Order Influence Functions: Statistical Theory of a Class of Bilinear Forms
Na Liu, Chang Li, Yujia Gu +1
Higher-order influence functions, introduced in a series of articles (Robins et al., 2008, 2009a; van der Vaart, 2014; Robins et al., 2016, 2023; Liu et al., 2017), are a unified f…
On the Asymptotic Inadmissibility of Double Machine Learning Estimators Under Structure-Agnostic Models
Lin Liu, Rajarshi Mukherjee, James M Robins
Structure-agnostic (SA) models introduced by Balakrishnan et al. (2026) aim to reflect the general lack of knowledge of structural assumptions on data-generating laws such as smoot…
Order Dependence in Regression by Composition: Discussion on "Regression by Composition'' by Farewell, Daniel, Stensrud, and Huitfeldt
Mei Dong, Linbo Wang, Lin Liu +1
We discuss the regression-by-composition framework of Farewell, Daniel, Stensrud and Huitfeldt, highlighting a key consequence of its sequential construction: order dependence. Reo…
A Parameter-Centric View on Regression
Jingxin Yan, Lin Liu, Oliver Dukes +2
Discussion on ``Regression by Composition'' by Farewell, Daniel, Stensrud, and Huitfeldt
Toward Variation-Independent Regression by Composition
Ruixuan Zhao, Oliver Dukes, Linbo Wang +1
Discussion on "Regression by Composition" by Farewell, Daniel, Stensrud, and Huitfeldt.