Harding Professor of Statistics in Public Life
Research Interests: Statistics: in particular Functional / Object Data Analysis, Time Series Analysis, Official and Public Policy Statistics, Statistical Neuroimaging, Statistical Linguistics, Seasonal Adjustment and other Applied Statistics
Publications
Rejoinder for “A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain”
– Journal of the American Statistical Association
(2019)
114,
1103
Statistical Analysis of Functions on Surfaces, With an Application to Medical Imaging
– Journal of the American Statistical Association
(2019)
115,
1420
A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain
– ournal of the American Statistical Association (Theory & Methods)
(2019)
114,
1081
Aβ-induced vulnerability propagates via the brain’s default mode network
– Nature Communications
(2019)
10,
2353
(doi: 10.1038/s41467-019-10217-w)
Publisher Correction: Accurate autocorrelation modeling substantially improves fMRI reliability
– Nature Communications
(2019)
10,
1511
(doi: 10.1038/s41467-019-09619-7)
Accurate autocorrelation modeling substantially improves fMRI reliability.
– Nature Communications
(2019)
10,
1220
(doi: 10.1038/s41467-019-09230-w)
A data-centric bottom up model for generation of stochastic internal load profiles based on space-use type
– Journal of Building Performance Simulation
(2019)
12,
620
Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers
– IEEE Journal of Selected Topics in Signal Processing
(2018)
12,
1615
(doi: 10.1109/jstsp.2018.2876995)
The Statistical Analysis of Acoustic Phonetic Data: Exploring Differences Between Spoken Romance Languages
– Journal of the Royal Statistical Society. Series C: Applied Statistics
(2018)
67,
1103
(doi: 10.1111/rssc.12258)
Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models
– Journal of Machine Learning Research
(2018)
19,
1
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