Publications
Publications
X. Tian, A. Gibberd, M. Nunes, S.Roy. Multi-response linear regression estimation based on low-rank pre-smoothing, ArXiV Preprint, 2024 (link)
K. S. Nobari, A. Gibberd. ℓ1-Regularized Generalized Least Squares, ArXiV Preprint, 2024 (link)
C. Pinkney, C. Euan, A. Gibberd, A. Shojaie. Regularised Spectral Estimation for High-Dimensional Point Processes, ArXiV Preprint, 2024 (link)
L. Mosley, T. T. Chan, A. Gibberd. SparseDFM: An R Package to Estimate Dynamic Factor Models with Sparse Loadings. ArXiV Preprint, 2023 (link)
S. Chrétien, A. Gibberd, S. Roy. Hedging parameter selection for basis pursuit. In prep., 2018 (Technical note)
A. Gibberd and S Roy. Multiple Changepoint Estimation in High-Dimensional Gaussian Graphical Models. Working Paper, 2018 (link)
L. Mosley, K. S. Nobari, G. Brandi , A. Gibberd. Disaggregating Time-Series with Many Indicators: An Overview of the DisaggregateTS Package, The R Journal, 2025 (link)
T. T. Chan and A. Gibberd. Feasible model-based principal component analysis: Joint estimation of rank and error covariance matrix. Computational Statistics and Data Analysis, 2024 (link)
L. Mosley, T. T. Chan, and A. Gibberd. The sparse dynamic factor model: a regularised quasi-maximum likelihood approach. Statistics and Computing, 2024 (link)
W. Qiao, D. Bu, A. Gibberd, Y. Liao, T. Wen, E. Li. When “time varying” volatility meets “transaction cost” in portfolio selection. Journal of Empirical Finance, 2023
K. Ferentinos, A. Gibberd, and B. Guin. Stranded houses? The price effect of a minimum energy efficiency standard. Energy Economics, 2023
L. Mosley, I. Eckley, and A. Gibberd. Sparse Temporal Disaggregation. Journal of the Royal Statistical Society: Series A, 2022
E.A.K. Cohen and A. Gibberd. Wavelet Spectra for Multivariate Point Processes. Biometrika, 2021
R. P. Monti, A. Gibberd, S. Roy, M. Nunes, T. Ogawa, M. Kawanabe, R. Lorenz, R. Leech, and A. Hyvarinen. Interpretable Brain Age Prediction using Linear Latent Variable Models of Functional Connectivity. PLOS ONE, 2020
A. Gibberd and S. Roy. Consistent Multiple Changepoint Estimation with Fused Gaussian Graphical Models. Annals of the Institute of Statistical Mathematics, 2020
J.D.B. Nelson, A. Gibberd, C. Nafornita, and N. Kingsbury. The locally stationary dual-tree complex wavelet model. Statistics and Computing, 2017
A. Gibberd and J.D.B. Nelson. Regularized Estimation of Piecewise Constant Gaussian Graphical Models: The Group-Fused Graphical Lasso. Journal of Computational and Graphical Statistics (JCGS), 2017
A. Gibberd and J.D.B. Nelson. Estimating Dynamic Graphical Models from Multivariate Time-Series Data: Recent Methods and Results. In Lecture Notes in Computer Science, 2016
T. T. Chan and A. Gibberd. Identifying Metering Hierarchies with Distance Correlation and Dominance Constraints. In IEEE 21st International Conference of Machine Learning and Applications (ICMLA), 2022
A. Gibberd and E.A.K. Cohen. Temporally Smoothed Wavelet Coherence for Multivariate Point-Processes and Neuron-Firing. In IEEE 52nd Asilomar Conference on Signals, Systems, and Computers, 2018
A. Gibberd, J. Noble, and E.A.K. Cohen. Characterising Dependency in Computer Networks using Spectral Coherence. In International Conference on Time-series and Forecasting (ITISE), 2018
A. Gibberd, M. Evangelou, and J.D.B. Nelson. The Time-Varying Dependency Patterns of NetFlow Statistics. In IEEE International Conference on Data Mining Workshops (ICDMW), 2017
A. Gibberd and J.D.B. Nelson. Regularised estimation of 2D-locally stationary wavelet processes. In IEEE Workshop on Statistical Signal Processing Proceedings, 2016
J.D.B. Nelson and A. Gibberd. Introducing the Locally Stationary Dual-Tree Complex Wavelet Model. In IEEE International Conference on Image Processing (ICIP), 2016
A. Gibberd and J.D.B. Nelson. Estimating multiresolution dependency graphs within the stationary wavelet framework. In IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2016
A. Gibberd and J.D.B. Nelson. Sparsity in the multivariate wavelet framework: a comparative study using epileptic electroencephalography data. In International Conference on Intelligent Signal Processing (IET ISP), 2015
A. Gibberd and J.D.B. Nelson. Estimating dynamic graphical models from multivariate time-series data. In European Conference on Machine Learning - Advanced Analysis and Learning on Temporal Data (LNCS), 2015
A. Gibberd and J.D.B. Nelson. High dimensional changepoint detection with a dynamic graphical lasso. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014