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Outputs (25)

Object oriented data analysis of surface motion time series in peatland landscapes (2024)
Journal Article
Mitchell, E. G., Dryden, I. L., Fallaize, C. J., Andersen, R., Bradley, A. V., Large, D. J., & Sowter, A. (2024). Object oriented data analysis of surface motion time series in peatland landscapes. Journal of the Royal Statistical Society: Series C, Article qlae060. https://doi.org/10.1093/jrsssc/qlae060

Peatlands account for 10% of UK land area, 80% of which are degraded to some degree, emitting carbon at a similar magnitude to oil refineries or landfill sites. A lack of tools for rapid and reliable assessment of peatland condition has limited monit... Read More about Object oriented data analysis of surface motion time series in peatland landscapes.

Manifold valued data analysis of samples of networks, with applications in corpus linguistics (2022)
Journal Article
Severn, K. E., Dryden, I. L., & Preston, S. P. (2022). Manifold valued data analysis of samples of networks, with applications in corpus linguistics. Annals of Applied Statistics, 16(1), 368-390. https://doi.org/10.1214/21-aoas1480

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
Seymour, R. G., Sirl, D., Preston, S. P., Dryden, I. L., Ellis, M. J., Perrat, B., & Goulding, J. (2022). The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania. Journal of the Royal Statistical Society: Series C, 71(2), 288-308. https://doi.org/10.1111/rssc.12532

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
Louison, K. A., Louison, K. A., Dryden, I. L., & Laughton, C. A. (2021). GLIMPS: A Machine Learning Approach to Resolution Transformation for Multiscale Modeling. Journal of Chemical Theory and Computation, 17(12), 7930-7937. https://doi.org/10.1021/acs.jctc.1c00735

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
Severn, K. E., Dryden, I. L., & Preston, S. P. (2021). Non‐parametric regression for networks. Stat, 10(1), Article e373. https://doi.org/10.1002/sta4.373

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.

Regression modelling for size-and-shape data based on a Gaussian model for landmarks (2020)
Journal Article
Dryden, I. L., Kume, A., Paine, P. J., & Wood, A. T. A. (2021). Regression modelling for size-and-shape data based on a Gaussian model for landmarks. Journal of the American Statistical Association, 116(534), 1011-1022. https://doi.org/10.1080/01621459.2020.1724115

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
Dryden, I. L., Kim, K.-R., Laughton, C. A., & Le, H. (2019). Principal nested shape space analysis of molecular dynamics data. Annals of Applied Statistics, 13(4), 2213-2234. https://doi.org/10.1214/19-AOAS1277

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
Varano, V., Piras, P., Gabriele, S., Teresi, L., Nardinocchi, P., Dryden, I. L., Torromeo, C., Schiariti, M., & Puddu, P. E. (2020). Local and Global Energies for Shape Analysis in Medical Imaging. International Journal for Numerical Methods in Biomedical Engineering, 36(2), Article e3252. https://doi.org/10.1002/cnm.3252

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.

Bayesian linear size-and-shape regression with applications to face data (2018)
Journal Article
Dryden, I. L., Le, H., & Kim, K.-R. (2019). Bayesian linear size-and-shape regression with applications to face data. Sankhya A, 81(1), 83–103. https://doi.org/10.1007/s13171-018-0136-8

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.