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Department of Pure Mathematics and Mathematical Statistics

Professor of Mathematical Statistics

Research Interests: Mathematical Statistics: nonparametric and high-dimensional inference, Bayesian nonparametrics, statistical inverse problems, empirical process theory

Publications

Efficient estimation of linear functionals of principal components
V Koltchinskii, M Loffler, R Nickl
– The Annals of Statistics
(2020)
48,
464
Efficient nonparametric Bayesian inference for $X$-ray transforms
F Monard, R Nickl, GP Paternain
– Annals of Statistics
(2019)
47,
1113
A Conversation with Dick Dudley
V Koltchinskii, R Nickl, P Rigollet
– Statistical Science
(2019)
34,
169
Uncertainty Quantification for Matrix Compressed Sensing and Quantum Tomography Problems
A Carpentier, J Eisert, D Gross, R Nickl
– pp
(2019)
3,
385
Uncertainty Quantification for Matrix Compressed Sensing and Quantum Tomography Problems
A Carpentier, J Eisert, D Gross, R Nickl
(2019)
74,
385
Bernstein–von Mises theorems for statistical inverse problems II: compound Poisson processes
R Nickl, J Söhl
– Electronic Journal of Statistics
(2019)
13,
3513
Adaptive confidence sets for matrix completion.
A Carpentier, O Klopp, M Löffler, R Nickl
– Bernoulli
(2018)
24,
2429
Inference on covariance operators via concentration inequalities: K-sample tests, classification, and clustering via rademacher complexities
AB Kashlak, JAD Aston, R Nickl
– Sankhya A
(2019)
81,
214
Comments on: High-dimensional simultaneous inference with the bootstrap
M Löffler, R Nickl
– Test
(2017)
26,
731
Nonparametric Bayesian posterior contraction rates for discretely observed scalar diffusions
R Nickl, J Söhl
– Annals of Statistics
(2017)
45,
1664
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Room

D2.05

Telephone

01223 765020