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math.ST2025
Latent confounding in high-dimensional nonlinear models
Yuhao Wang, Rajen Shah
We consider the the problem of identifying causal effects given a high-dimensional treatment vector in the presence of low-dimensional latent confounders. We assume a parametric st…
math.ST2025
Average partial effect estimation using double machine learning
Harvey Klyne, Rajen D. Shah
Single-parameter summaries of variable effects in regression settings are desirable for ease of interpretation. However (partially) linear models for example, which would deliver t…
math.ST2024
ROSE Random Forests for Robust Semiparametric Efficient Estimation
Elliot H. Young, Rajen D. Shah
It is widely recognised that semiparametric efficient estimation can be hard to achieve in practice: estimators that are in theory efficient may require unattainable levels of accu…