I am a Reader in the Department of Mathematics, Imperial College London.

My research interests are primarily in statistical theory, particularly the implications of and means of inducing population-level sparsity, with a view to achieving reconciliation between low-dimensional Fisherian foundations and modern high-dimensional problems. See Battey (2023) for a summary of some of my work in this vein.


h.battey@imperial.ac.uk




PhD students

Rebecca Lewis
Jakub Rybak

Pre-doctoral research supervision

Su Hyeong Lee (Undergraduate Research Opportunities Programme 2020)
Joanna Lada (Mary Lister McCammon scholar 2019)
Jakub Rybak (MSc research dissertation 2019)
Rebecca Lewis (Undergraduate Research Opportunities Programme 2018)

Research funding

EPSRC Early Career Research Fellowship, Oct 2020 - Sep 2025.
Theoretical foundations of inference in the presence of a large number of nuisance parameters.
EPSRC Postdoctoral Research Fellowship, Jan 2017 - Dec 2019.
Inference for functions of large covariance matrices.

Editorial affiliations etc

Biometrika
Information and Inference: a Journal of the IMA
Journal of the American Statistical Association
Journal of the Royal Statistical Society, Series B

Honorary Secretary of the Research Section Committee
(Associate Editor for Series B discussion papers).

Trustee of the Fisher Memorial Trust.

Biographical outline

2016-present: Lecturer then Reader, Imperial College London, UK
2014-2016: Research Fellow, Princeton University, USA
2011-2014: Brunel Fellow in Statistics, University of Bristol, UK
2008-2011: PhD, University of Cambridge, UK

Discussion contributions and commissioned material

Battey, H. S. (2023)
D. R. Cox: extracts from a memorial lecture.
Harvard Data Science Review, 5 (2).

Battey, H. S. (2022)
D. R. Cox Memorial Lecture.
JSM Proceedings, Washington DC, 635-639.

Battey, H. S. (2022)
Discussion of Assumption-lean inference for generalised linear model parameters by Vansteelandt and Dukes.
J. R. Statist. Soc. Ser. B, 84, 696-698.

Battey, H. S. and Reid, N. (2022)
Obituary: David Cox
IMS Bulletin, 51 (3), 14-16.

Battey, H. S. and Cox, D. R. (2022)
Aspects of non-standard multivariate analysis.
J. Multivar. Analysis -- invited contribution to the 50th anniversary issue, 188, 104810.


Publications in statistical theory

Battey, H. S. (2023)
Inducement of population sparsity.
Canadian J. Statist. -- Festschrift in honour of Nancy Reid, to appear.

Battey, H. S., Cox, D. R. and Lee, S. (2023)
On partial likelihood and the construction of factorisable transformations.
Information Geometry, to appear.

Ward, S., Battey, H. S. and Cohen, E.A.K. (2023)
Estimation of the intensity function of a spatial point process on a Riemannian manifold.
Biometrika, to appear.

Battey, H. S. and Reid, N. (2023)
On inference in high-dimensional regression.
J. R. Statist. Soc. Ser. B, 85, 149-175. [matlab implementation]

Battey, H. S. and Cox, D. R. (2023)
Missing observations in regression: a conditional approach.
Royal Society Open Science, 10, 220267. [matlab implementation]

Battey, H. S. and Cox, D. R. (2022)
Some perspectives on inference in high dimensions.
Statistical Science, 37, 110-122.

Tan, K. M., Battey, H. S. and Zhou, W-X. (2022)
Communication-constrained quantile regression with statistical guarantees.
J. Machine Learning Research, 23, 1-61.

Rybak, J. and Battey, H. S. (2021)
Sparsity induced by covariance transformation: some deterministic and probabilistic results.
Proc. Roy. Soc. London A, 477, 20200756.

Battey, H. S. (2021)
A note on the analytic approximation of exceedance probabilities in heterogeneous populations.
Statist. Probab. Lett., 179, 109215.

Nieto-Reyes, A. and Battey, H. S. (2021)
A topologically valid construction of depth for functional data.
J. Multivariate Analysis, 184, 104738.

Battey, H. S. and Cox, D. R. (2020)
High-dimensional nuisance parameters: an example from parametric survival analysis.
Information Geometry, 3, 119-148.

Battey, H. S. (2019)
On sparsity scales and covariance matrix transformations.
Biometrika, 106, 605-617.

Battey, H. S., Cox, D. R. and Jackson, M. V. (2019)
On the linear in probability model for binary data.
Royal Society Open Science, 6, 190067. [matlab implementation]

Battey, H. S. and Cox, D. R. (2018)
Large numbers of explanatory variables: a probabilistic assessment.
Proc. Roy. Soc. London A, 474, 20170631. [software].

Avella, M., Battey, H. S., Fan, J. and Li, Q. (2018)
Robust estimation of high-dimensional covariance and precision matrices.
Biometrika, 105, 271-284.

Battey, H. S., Fan, J., Liu, Lu and Zhu, Z. (2018)
Distributed testing and estimation in sparse high dimensional models.
Ann. Statist., 46, 1352-1382.

Cox, D. R. and Battey, H. S. (2017)
Large numbers of explanatory variables, a semi-descriptive analysis.
Proc. Nat. Acad. Sci., 114 (32), 8592-8595. [software].

Battey, H. S. (2017)
Eigen structure of a new class of structured covariance and inverse covariance matrices.
Bernoulli, 23, 3166-3177.

Nieto-Reyes, A. and Battey, H. S. (2016)
A topologically valid definition of depth for functional data.
Statistical Science, 31 61-79.

Battey, H. S., Feng, Q. and Smith, R. J. (2016)
Improving confidence set estimation when parameters are weakly identified.
Statist. Probab. Lett., 118 117-123.

Battey, H. S. and Linton, O. B. (2014)
Nonparametric estimation of multivariate elliptic densities via mixture sieves.
J. Multivar. Analysis, 123 43-67.

Battey, H. S. and Sancetta, A. (2013)
Conditional estimation for dependent functional data.
J. Multivar. Analysis, 120 1-17.


Mathematical modelling of complex systems

Beale, N., Battey, H. S., Davison, A. C. and MacKay, R. S. (2020)
An unethical optimization principle.
Royal Society Open Science, 7, 200462.

Beale, N., Rand, D., Battey, H., Croxson, May, R. M., Nowak, M. A. (2011)
Individual versus systemic risk and the Regulator's Dilemma.
Proc. Nat. Acad. Sci., 108 (31) 12647-12652


Applied and computational work

Castagno, S. and five others including Battey, H. S. (2021)
Seizure outcomes of temporoparietooccipital and frontal disconnection in children with drug-resistant epilepsy.
Epilepsy Research, 177, 106769.

Hoeltgebaum, H. H. and Battey, H. S. (2019)
HCmodelSets: An R package for specifying sets of well-fitting models in high dimensions.
The R Journal, 11, 370-379.