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Department of Pure Mathematics and Mathematical Statistics

 

Professor (Grade 11)

Research Interests: High-dimensional statistics and large-scale data analysis

 

Publications

The Projected Covariance Measure for assumption-lean variable significance testing
AR Lundborg, I Kim, RD Shah, RJ Samworth
(2022)
Conditional independence testing in Hilbert spaces with applications to functional data analysis
AR Lundborg, RD Shah, J Peters
– Journal of the Royal Statistical Society. Series B: Statistical Methodology
(2022)
High-dimensional regression with potential prior information on variable importance
BG Stokell, RD Shah
– Statistics and Computing
(2022)
32,
52
Structure Learning for Directed Trees
ME Jakobsen, RD Shah, P Bühlmann, J Peters
– Journal of Machine Learning Research
(2022)
23,
Cross-validation for change-point regression: pitfalls and solutions
F Pein, RD Shah
(2021)
Modelling high‐dimensional categorical data using nonconvex fusion penalties
BG Stokell, RD Shah, RJ Tibshirani
– Journal of the Royal Statistical Society. Series B: Statistical Methodology
(2021)
83,
579
Bets: The dangers of selection bias in early analyses of the coronavirus disease (covid-19) pandemic
Q Zhao, N Ju, S Bacallado, RD Shah
– Annals of Applied Statistics
(2021)
15,
363
Conditional Independence Testing in Hilbert Spaces with Applications to Functional Data Analysis
AR Lundborg, RD Shah, J Peters
(2021)
Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders
Y Wang, RD Shah
(2020)
The Hardness of Conditional Independence Testing and the Generalised Covariance Measure
RD Shah, J Peters
– The Annals of Statistics
(2020)
48,
1514
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Room

D1.15

Telephone

01223 765923