Outputs (31)

Manifold valued data analysis of samples of networks, with applications in corpus linguistics (2022)
Journal Article

Networks arise in many applications, such as in the analysis of text documents, social interactions and brain activity. We develop a general framework for extrinsic statistical analysis of samples of networks, motivated by networks representing text... Read More about Manifold valued data analysis of samples of networks, with applications in corpus linguistics.

The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania (2022)
Journal Article

Identifying the most deprived regions of any country or city is key if policy makers are to design successful interventions. However, locating areas with the greatest need is often surprisingly challenging in developing countries. Due to the logistic... Read More about The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania.

GLIMPS: A Machine Learning Approach to Resolution Transformation for Multiscale Modeling (2021)
Journal Article

We describe a general approach to transforming molecular models between different levels of resolution, based on machine learning methods. The approach uses a matched set of models at both levels of resolution for training, but requires only the coor... Read More about GLIMPS: A Machine Learning Approach to Resolution Transformation for Multiscale Modeling.

Non?parametric regression for networks (2021)
Journal Article

Network data are becoming increasingly available, and so there is a need to develop suitable methodology for statistical analysis. Networks can be represented as graph Laplacian matrices, which are a type of manifold-valued data. Our main objective i... Read More about Non?parametric regression for networks.

Discovery of synergistic material-topography combinations to achieve immunomodulatory osteoinductive biomaterials using a novel in vitro screening method: The ChemoTopoChip (2021)
Journal Article

© 2021 The Authors Human mesenchymal stem cells (hMSCs) are widely represented in regenerative medicine clinical strategies due to their compatibility with autologous implantation. Effective bone regeneration involves crosstalk between macrophages an... Read More about Discovery of synergistic material-topography combinations to achieve immunomodulatory osteoinductive biomaterials using a novel in vitro screening method: The ChemoTopoChip.

Smoothing splines on Riemannian manifolds, with applications to 3D shape space (2020)
Journal Article

© 2020 The Authors. Journal of the Royal Statistical Society: Series B (Statistical Methodology) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society There has been increasing interest in statistical analysis of data lying in m... Read More about Smoothing splines on Riemannian manifolds, with applications to 3D shape space.

Regression modelling for size-and-shape data based on a Gaussian model for landmarks (2020)
Journal Article

In this paper we propose a regression model for size-and-shape response data. So far as we are aware, few such models have been explored in the literature to date. We assume a Gaussian model for labelled landmarks; these landmarks are used to represe... Read More about Regression modelling for size-and-shape data based on a Gaussian model for landmarks.

Principal nested shape space analysis of molecular dynamics data (2019)
Journal Article

Molecular dynamics simulations produce huge datasets of temporal sequences of molecules. It is of interest to summarize the shape evolution of the molecules in a succinct, low-dimensional representation. However, Euclidean techniques such as principa... Read More about Principal nested shape space analysis of molecular dynamics data.

Local and Global Energies for Shape Analysis in Medical Imaging (2019)
Journal Article

In a previous contribution a new Riemannian shape space, named TPS space, was introduced to perform statistics on shape data. This space was endowed with a Rie-mannian metric and a flat connection, with torsion, compatible with the given metric. This... Read More about Local and Global Energies for Shape Analysis in Medical Imaging.

Discussion: Object-Oriented Data Analysis, Power Metrics, and Graph Laplacians (2019)
Journal Article

Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17??ethinylestradiol (2019)
Journal Article

Mathematical modelling can play a key role in understanding as well as quantifying uncertainties surrounding the presence and fate of emerging pollutants in wastewater treatment processes (WWTPs). This paper presents for the first time a simplified e... Read More about Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17??ethinylestradiol.

Bayesian linear size-and-shape regression with applications to face data (2018)
Journal Article

Regression models for size-and-shape analysis are developed, where the model is specified in the Euclidean space of the landmark coordinates. Statistical models in this space (which is known as the top space or ambient space) are often easier for pra... Read More about Bayesian linear size-and-shape regression with applications to face data.

Peptide refinement using a stochastic search (2018)
Journal Article

Identifying a peptide based on a scan from a mass spectrometer is an important yet highly challenging problem. To identify peptides, we present a Bayesian approach which uses prior information about the average relative abundances of bond cleavages a... Read More about Peptide refinement using a stochastic search.

Multiple linear regression modelling to predict the stability of polymer-drug solid dispersions: comparison of the effects of polymers and manufacturing methods on solid dispersion stability (2018)
Journal Article

Solid dispersions can be a successful way to enhance the bioavailability of poorly soluble drugs. Here 60 solid dispersion formulations were produced using ten chemically diverse, neutral, poorly soluble drugs, three commonly used polymers, and two m... Read More about Multiple linear regression modelling to predict the stability of polymer-drug solid dispersions: comparison of the effects of polymers and manufacturing methods on solid dispersion stability.

Journeys in big data statistics (2018)
Journal Article

The realm of big data is a very wide and varied one. We discuss old, new, small and big data, with some of the important challenges including dealing with highly-structured and object-oriented data. In many applications the objective is to discern pa... Read More about Journeys in big data statistics.

The decomposition of deformation: new metrics to enhance shape analysis in medical imaging (2018)
Journal Article

In landmarks-based Shape Analysis size is measured, in most cases, with Centroid Size. Changes in shape are decomposed in affine and non affine components. Furthermore the non affine component can be in turn decomposed in a series of local deformatio... Read More about The decomposition of deformation: new metrics to enhance shape analysis in medical imaging.

Penalised Euclidean distance regression (2018)
Journal Article

A method is introduced for variable selection and prediction in linear regression problems where the number of predictors can be much larger than the number of observations. The methodology involves minimising a penalised Euclidean distance, where th... Read More about Penalised Euclidean distance regression.

Decoding fMRI events in sensorimotor motor network using sparse paradigm free mapping and activation likelihood estimates: Decoding fMRI Events in SMN (2017)
Journal Article

Most functional MRI (fMRI) studies map task-driven brain activity using a block or event-related paradigm. Sparse paradigm free mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information,... Read More about Decoding fMRI events in sensorimotor motor network using sparse paradigm free mapping and activation likelihood estimates: Decoding fMRI Events in SMN.

Linear discriminant analysis reveals differences in root architecture in wheat seedlings related to nitrogen uptake efficiency (2017)
Journal Article

© The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. Root architecture impacts water and nutrient uptake efficiency. Identifying exactly which root architectural properties influence these agronom... Read More about Linear discriminant analysis reveals differences in root architecture in wheat seedlings related to nitrogen uptake efficiency.

The TPS Direct Transport: a new method for transporting deformations in the Size-and-shape Space (2017)
Journal Article

Modern shape analysis allows the fine comparison of shape changes occurring between different objects. Very often the classic machineries of Generalized Procrustes Analysis and Principal Component Analysis are used in order to contrast the shape chan... Read More about The TPS Direct Transport: a new method for transporting deformations in the Size-and-shape Space.

Covariance analysis for temporal data, with applications to DNA modelling (2017)
Journal Article

We introduce methodology for analysing the mean size-and-shape and covariance matrix of landmark data that are collected over time. Motivated by a study of DNA damage, we study some permutation based tests for investigating significant differences in... Read More about Covariance analysis for temporal data, with applications to DNA modelling.

Participatory modelling for stakeholder involvement in the development of flood risk management intervention options (2016)
Journal Article

Advancing stakeholder participation beyond consultation offers a range of benefits for local flood risk management, particularly as responsibilities are increasingly devolved to local levels. This paper details the design and implementation of a par... Read More about Participatory modelling for stakeholder involvement in the development of flood risk management intervention options.

Regularisation, interpolation and visualisation of diffusion tensor images using non-Euclidean statistics (2015)
Journal Article

Practical statistical analysis of diffusion tensor images is considered, and we focus primarily on methods that use metrics based on Euclidean distances between powers of diffusion tensors. First we describe a family of anisotropy measures based on a... Read More about Regularisation, interpolation and visualisation of diffusion tensor images using non-Euclidean statistics.

Long-term amorphous drug stability predictions using easily calculated, predicted, and measured parameters (2015)
Journal Article

Bayesian registration of functions and curves (2015)
Journal Article

Bayesian analysis of functions and curves is considered, where warping and other geometrical transformations are often required for meaningful comparisons. The functions and curves of interest are represented using the recently introduced square root... Read More about Bayesian registration of functions and curves.

Covariance weighted procrustes analysis (2015)
Book Chapter

© Springer International Publishing Switzerland 2016. We revisit the popular Procrustes matching procedure of landmark shape analysis and consider the situation where the landmark coordinates have a completely general covariance matrix, extending pre... Read More about Covariance weighted procrustes analysis.

Size and shape analysis of error-prone shape data (2014)
Journal Article

We consider the problem of comparing sizes and shapes of objects when landmark data are prone to measurement error. We show that naive implementation of ordinary Procrustes analysis that ignores measurement error can compromise inference. To account... Read More about Size and shape analysis of error-prone shape data.

Distances and inference for covariance operators (2014)
Journal Article

A framework is developed for inference concerning the covariance operator of a functional random process, where the covariance operator itself is an object of interest for statistical analysis. Distances for comparing positive-definite covariance mat... Read More about Distances and inference for covariance operators.

Rank-based model selection for multiple ions quantum tomography (2012)
Journal Article

The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and th... Read More about Rank-based model selection for multiple ions quantum tomography.

A Bayesian elicitation of veterinary beliefs regarding systemic dry cow therapy: variation and importance for clinical trial design (2012)
Journal Article

The two key aims of this research were: (i) to conduct a probabilistic elicitation to quantify the variation in veterinarians’ beliefs regarding the efficacy of systemic antibiotics when used as an adjunct to intra-mammary dry cow therapy and (ii) to... Read More about A Bayesian elicitation of veterinary beliefs regarding systemic dry cow therapy: variation and importance for clinical trial design.

Bayesian alignment of continuous molecular shapes using random fields (2008)
Journal Article

Statistical methodology is proposed for comparing molecular shapes. In order to account for the continuous nature of molecules, classical shape analysis methods are combined with techniques used for predicting random fields in spatial statistics. Ap... Read More about Bayesian alignment of continuous molecular shapes using random fields.