Browsing Department of Pure Mathematics and Mathematical Statistics (DPMMS) by Author "Aston, John Alexander"
Now showing items 1-7 of 7
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A Functional Approach to Deconvolve Dynamic Neuroimaging Data
Jiang, CR; Aston, John Alexander; Wang, JL (Taylor & FrancisJournal of the American Statistical Association, 2015-11-20)Positron Emission Tomography (PET) is an imaging technique which can be used to investigate chemical changes in human biological processes such as cancer development or neurochemical reactions. Most dynamic PET scans are ...
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Gaussian tree constraints applied to acoustic linguistic functional data
Shiers, Nathaniel; Aston, John Alexander; Smith, Jim Q; Coleman, John S (ElsevierJournal of Multivariate Analysis, 2016-10-11)Evolutionary models of languages are usually considered to take the form of trees. With the development of so-called tree constraints the plausibility of the tree model assumptions can be assessed by checking whether the ...
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Minimax optimal procedures for testing the structure of multidimensional functions
Aston, John Alexander; Autin, F; Claeskens, G; Freyermuth, J-M; Pouet, CWe present a novel method for detecting some structural characteristics of multidimensional functions. We consider the multidimensional Gaussian white noise model with an anisotropic estimand. Using the relation between ...
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SMOOTH PRINCIPAL COMPONENT ANALYSIS OVER TWO-DIMENSIONAL MANIFOLDS WITH AN APPLICATION TO NEUROIMAGING
Lila, Eardi; Aston, John Alexander; Sangalli, Laura M (Institute of Mathematical StatisticsThe Annals of Applied Statistics, 2016-01-05)Motivated by the analysis of high-dimensional neuroimaging signals located over the cortical surface, we introduce a novel Principal Component Analysis technique that can handle functional data located over a two-dimensional ...
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Tests for separability in nonparametric covariance operators of random surfaces
Aston, John Alexander; Pigoli, Davide; Tavakoli, Shahin (Institute of Mathematical StatisticsAnnals of Statistics, 2016)The assumption of separability of the covariance operator for a random image or hypersurface can be of substantial use in applications, especially in situations where the accurate estimation of the full covariance structure ...
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Towards Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach
Zhou, Yan; Johansen, Adam M; Aston, John Alexander (Taylor & FrancisJournal of Computational and Graphical Statistics, 2015-08-17)Model comparison for the purposes of selection, averaging and validation is a problem found throughout statistics. Within the Bayesian paradigm, these problems all require the calculation of the posterior probabilities of ...
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Unifying Amplitude and Phase Analysis Unifying Amplitude and Phase Analysis. A Compositional Data Approach to Functional Multivariate Mixed-Effects Modeling of Mandarin Chinese
Hadjipantelis, PZ; Aston, John Alexander; Müller, HG; Evans, JP (Taylor & FrancisJournal of the American Statistical Association, 2015-07-06)Mandarin Chinese is characterized by being a tonal language; the pitch (or F0) of its utterances carries considerable linguistic information. However, speech samples from different individuals are subject to changes in ...