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08/17/2023
Average partial effect estimation using double machine learning
Single-parameter summaries of variable effects are desirable for ease of...
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07/21/2023
Sandwich Boosting for Accurate Estimation in Partially Linear Models for Grouped Data
We study partially linear models in settings where observations are arra...
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01/06/2023
Rank-transformed subsampling: inference for multiple data splitting and exchangeable p-values
Many testing problems are readily amenable to randomised tests such as t...
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11/03/2022
The Projected Covariance Measure for assumption-lean variable significance testing
Testing the significance of a variable or group of variables X for predi...
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12/06/2021
Cross-validation for change-point regression: pitfalls and solutions
Cross-validation is the standard approach for tuning parameter selection...
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09/23/2021
High-dimensional regression with potential prior information on variable importance
There are a variety of settings where vague prior information may be ava...
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08/19/2021
Structure Learning for Directed Trees
Knowing the causal structure of a system is of fundamental interest in m...
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01/18/2021
Conditional Independence Testing in Hilbert Spaces with Applications to Functional Data Analysis
We study the problem of testing the null hypothesis that X and Y are con...
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11/17/2020
Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders
We consider estimation of average treatment effects given observational ...
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02/28/2020
Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties
We propose a method for estimation in high-dimensional linear models wit...
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09/24/2019
Double-estimation-friendly inference for high-dimensional misspecified models
All models may be wrong—but that is not necessarily a problem for infere...
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08/09/2019
Goodness-of-fit testing in high-dimensional generalized linear models
We propose a family of tests to assess the goodness-of-fit of a high-dim...
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11/02/2018
RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding
In this work we consider the problem of estimating a high-dimensional p ...
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04/19/2018
The Hardness of Conditional Independence Testing and the Generalised Covariance Measure
It is a common saying that testing for conditional independence, i.e., t...
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10/17/2016
The xyz algorithm for fast interaction search in high-dimensional data
When performing regression on a dataset with p variables, it is often of...
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08/06/2013
