Most of the members of this group are from the Statistics Section and Biomaths research group of the Department of Mathematics. Below you can find a list of research areas that members of this group are currently working on and/or would like to work on by applying their developed mathematical and statistical methods.

Research areas

Research areas


Publications

Citation

BibTex format

@article{Battey:2019,
author = {Battey, HS},
journal = {Biometrika},
title = {On sparsity scales and covariance matrix transformations},
url = {http://hdl.handle.net/10044/1/66425},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - We develop a theory of covariance and concentration matrix estimation on any given or es-timated sparsity scale when the matrix dimension is larger than the sample size. Non-standardsparsity scales are justified when such matrices are nuisance parameters, distinct from interest pa-rameters which should always have a direct subject-matter interpretation. The matrix logarithmicand inverse scales are studied as special cases, with the corollary that a constrained optimization-10based approach is unnecessary for estimating a sparse concentration matrix. It is shown throughsimulations that, for large unstructured covariance matrices, there can be appreciable advantagesto estimating a sparse approximation to the log-transformed covariance matrix and convertingthe conclusions back to the scale of interest.
AU - Battey,HS
PY - 2019///
SN - 0006-3444
TI - On sparsity scales and covariance matrix transformations
T2 - Biometrika
UR - http://hdl.handle.net/10044/1/66425
ER -