10 papers
The Debiased Score Test: Hunt-and-test for Semiparametric Hypotheses
Aditya Dhawan, F. Richard Guo, Rajen D. Shah
The parametric score test assesses a hypothesis through derivatives of the log-likelihood, whose expectation vanishes under the null. When the parameter of interest is a regression…
Aggregation of Statistical Evidence under Exchangeability
Antonin Schrab, Rajen Shah, Arthur Gretton +1
We study aggregation of statistical evidence under unknown and potentially complex dependence using group-invariance. Building on permutation-based constructions that treat transfo…
Outrigger local polynomial regression
Elliot H. Young, Rajen D. Shah, Richard J. Samworth
Standard local polynomial estimators of a nonparametric regression function employ a weighted least squares loss function that is tailored to the setting of homoscedastic Gaussian…
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…
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…
Change-point regression with a smooth additive disturbance
Florian Pein, Rajen D. Shah
We assume a nonparametric regression model where the signal is given by the sum of a piecewise constant function and a smooth function. To detect the change-points and estimate the…