Shape analysis; object oriented data analysis; manifold-valued data analysis; functional data analysis; networks; spatial statistics and statistical image analysis.
- Marron, J.S. and Dryden, I.L. (2022). Object-Oriented Data Analysis. CRC Press/ Chapman and Hall, Boca Raton. 424 + xii pages https://www.routledge.com/Object-Oriented-Data-Analysis/Marron-Dryden/p/book/9780815392828
- Dryden, I. L. and Mardia, K. V. (2016). Statistical Shape Analysis, with Applications in R (Second Edition) John Wiley, Chichester. 454 + xxiii pages. https://www.wiley.com/en-us/Statistical+Shape+Analysis%3A+With+Applications+in+R%2C+2nd+Edition-p-9780470699621
- Dryden, I. L. and Kent, J. T. (Editors) (2015). Geometry Driven Statistics. John Wiley, Chichester. 394 + xviii pages.
Some recent publications
- Severn, K. E., Dryden, I. L. and Preston, S. P. (2022). Manifold valued data analysis of samples of networks, with applications in corpus linguistics. Annals of Applied Statistics. To appear.
- Seymour, R.G., Sirl, D., Preston, S.P., Dryden, I.L., Ellis, M.J.A, Perrat, B. and Goulding, J. (2021). The Bayesian spatial Bradley–Terry model: urban deprivation modelling in Tanzania. Journal of the Royal Statistical Society, Series C (Applied Statistics). https://rss.onlinelibrary.wiley.com/doi/10.1111/rssc.12532
- Severn, K. E., Dryden, I. L. and Preston, S. P. (2021). Non-parametric regression for networks. Stat 10, e373 https://doi.org/10.1002/sta4.373
- Kim, K., Dryden, I.L., Le, H. and Severn, K.E. (2021). Smoothing splines on Riemannian manifolds, with applications to 3D shape space. Journal of the Royal Statistical Society, Series B (Methodology). 83, 108–132. https://doi.org/10.1111/rssb.12402
- Dryden, I.L., Kume, A., Paine, P.J. and 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, 1011–1022. https://doi.org/10.1080/01621459.2020.1724115
- Dryden, I.L. (2021). shapes package, R Foundation for Statistical Computing, Vienna, Austria, Contributed package. Version 1.2.6, March 31, 2021. https://cran.r-project.org/web/packages/shapes/index.html
- Louison, K. A., Dryden, I. L., and 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
- Dryden, I.L., Kim, K., Laughton, C.A. and Le, H. (2019). Principal nested shape space analysis of molecular dynamics data. Annals of Applied Statistics, 13, 2213–2234. https://doi.org/10.1214/19-AOAS1277
- Dryden, I.L., Kim, K. and Le, H. (2019). Bayesian linear size-and-shape regression with applications to face data. Sankhya A, 81, 83–103. https://doi.org/10.1007/s13171-018-0136-8
Links to citations and technical reports