John Aston

Functional Object Data Analysis and its Applications

EPSRC Funded Fellowship (2013-2018) on combining Functional Data Analysis, Trees and Manifold Data.

Project Outputs so far:

N Shiers, JAD Aston, JQ Smith and JS Coleman. Gaussian tree constraints applied to acoustic linguistic functional data, Journal of Multivariate Analysis, in press.

E Lila, JAD Aston, and LM Sangalli. Smooth Principal Component Analysis over two-dimensional manifolds with an application to Neuroimaging, Annals of Applied Statistics, in press.

F Lindsten, AM Johansen, CA Naesseth, B Kirkpatrick, TB Schön, JAD Aston, and A Bouchard-Côté. Divide-and-Conquer with Sequential Monte Carlo, Journal of Computational and Graphical Statistics in press.

H Sayal, JAD Aston, D Elliott and H Ombao. An Introduction to Applications of Wavelet Benchmarking with Seasonal Adjustment, Journal of the Royal Statistical Society, Series A, in press.

JAD Aston, D Pigoli and S Tavakoli. Tests for separability in nonparametric covariance operators of random surfaces, Annals of Statistics, in press.

Y Zhou, AM Johansen and JAD Aston. Towards Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach, Journal of Computational and Graphical Statistics, 25:701--726.

N Shiers, P Zwiernik, JAD Aston and JQ Smith. The correlation space of Gaussian latent tree models and model selection without fitting, Biometrika, 103: 531--545.

CR Jiang, JAD Aston and JL Wang. A functional approach to deconvolve dynamic neuroimaging data, Journal of the American Statistical Association, in press.

PZ Hadjipantelis, JAD Aston, HG Müller, and JP Evans. Unifying Amplitude and Phase Analysis: A Compositional Data Approach to Functional Multivariate Mixed-Effects Modeling of Mandarin Chinese, Journal of the American Statistical Association, in press.

CFH Nam, JAD Aston, I Eckley and R Killick. The Uncertainty of Storm Season Changes: Quantifying the Uncertainty of Autocovariance Changepoints, Technometrics, in press.

PZ Hadjipantelis, JAD Aston, HG Müller and J Moriarty. (2014) Analysis of spike train data: A multivariate mixed effects model for phase and amplitude. Electronic Journal of Statistics 8:1797--1807

G Minas, JAD Aston and N Stallard. (2014) Adaptive multivariate global testing, Journal of the American Statistical Association, 109:613--623. D Pigoli, JAD Aston, IL Dryden and P Secchi. (2014) Distances and Inference for Covariance Functions, Biometrika, 101:409--422..

CFH Nam, JAD Aston, and AM Johansen. (2014) Parallel Sequential Monte Carlo Samplers and Estimation of the Number of States in a Hidden Markov Model, Annals of the Institute of Statistical Mathematics, 66:553--575.

Some Background to the project:

JAD Aston and C Kirch. Estimation of the distribution of change-points with application to fMRI data (2012), Annals of Applied Statistics, 6:1906-1948,

PZ Hadjipantelis, JAD Aston and JP Evans. Characterizing fundamental frequency in Mandarin: A functional principal component approach utilizing mixed effect models (2012), Journal of the Acoustical Society of America, 131:4651-4664.

JAD Aston, D Buck, J Coleman, CJ Cotter, NS Jones, V Macaulay, N MacLeod, JM Moriarty and A Nevins (The Functional Phylogenies Group). Phylogenetic inference for function-valued traits: speech sound evolution (2012), Trends in Ecology and Evolution, 27:160-166.

Project Participants

Jean-Marc Freyermuth

Ah Yeon Park

Davide Pigoli

Shahin Tavakoli

Project Collaborators

John Coleman, Oxford Linguistics

Jonathan Evans, Academia Sinica, Linguistics

Frederic Ferraty, Toulouse, Statistics

Adam Johansen, Warwick, Statistics

Steve Marron, UNC, Statistics

Jim Smith, Warwick, Statistics

Federico Turkheimer, KCL, Neuroimaging

Last updated November 2016.