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Department of Pure Mathematics and Mathematical Statistics

 

Professor 

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

 

Publications

Change-point regression with a smooth additive disturbance
F Pein, RD Shah
(2021)
Cross-validation for change-point regression: pitfalls and solutions
F Pein, RD Shah
(2021)
Structure Learning for Directed Trees
ME Jakobsen, RD Shah, P Bühlmann, J Peters
(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
– The 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
– Annals of Statistics
(2020)
48,
1514
Goodness-of-fit testing in high dimensional generalized linear models
J Janková, RD Shah, P Bühlmann, RJ Samworth
– Journal of the Royal Statistical Society Series B Statistical Methodology
(2020)
82,
773
Right singular vector projection graphs: fast high dimensional covariance matrix estimation under latent confounding
RD Shah, B Frot, G-A Thanei, N Meinshausen
– Journal of the Royal Statistical Society Series B: Statistical Methodology
(2020)
82,
361
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Research Groups

Statistical Laboratory
Statistics

Room

D1.15

Telephone

01223 765923