All Outputs (16)

Structured prior distributions for the covariance matrix in latent factor models (2024)
Journal Article
Heaps, S. E., & Jermyn, I. H. (2024). Structured prior distributions for the covariance matrix in latent factor models. Statistics and Computing, 34(4), Article 143. https://doi.org/10.1007/s11222-024-10454-0

Factor models are widely used for dimension reduction in the analysis of multivariate data. This is achieved through decomposition of a p×p covariance matrix into the sum of two components. Through a latent factor representation, they can be interpre... Read More about Structured prior distributions for the covariance matrix in latent factor models.

A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields (2023)
Journal Article
Johnson, S. R., Heaps, S. E., Wilson, K. J., & Wilkinson, D. J. (2023). A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields. Environmetrics, 34(8), https://doi.org/10.1002/env.2824

With extreme weather events becoming more common, the risk posed by surface water flooding is ever increasing. In this work we propose a model, and associated Bayesian inference scheme, for generating short-term, probabilistic forecasts of localised... Read More about A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields.

A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant (2022)
Journal Article
Hannaford, N., Heaps, S., Nye, T., Curtis, T., Allen, B., Golightly, A., & Wilkinson, D. (2023). A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant. Computational Statistics & Data Analysis, 179, https://doi.org/10.1016/j.csda.2022.107659

Proper function of a wastewater treatment plant (WWTP) relies on maintaining a delicate balance between a multitude of competing microorganisms. Gaining a detailed understanding of the complex network of interactions therein is essential to maximisin... Read More about A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant.

Enforcing Stationarity through the Prior in Vector Autoregressions (2022)
Journal Article
Heaps, S. E. (2023). Enforcing Stationarity through the Prior in Vector Autoregressions. Journal of Computational and Graphical Statistics, 32(1), 74-83. https://doi.org/10.1080/10618600.2022.2079648

Stationarity is a very common assumption in time series analysis. A vector autoregressive process is stable if and only if the roots of its characteristic equation lie outside the unit circle, constraining the autoregressive coefficient matrices to l... Read More about Enforcing Stationarity through the Prior in Vector Autoregressions.

Incorporating compositional heterogeneity into Lie Markov models for phylogenetic inference (2020)
Journal Article
Hannaford, N. E., Heaps, S. E., Nye, T. M., Williams, T. A., & Embley, T. M. (2020). Incorporating compositional heterogeneity into Lie Markov models for phylogenetic inference. Annals of Applied Statistics, 14(4), 1964-1983. https://doi.org/10.1214/20-aoas1369

Generalizing rate heterogeneity across sites in statistical phylogenetics (2020)
Journal Article
Heaps, S. E., Nye, T. M., Boys, R. J., Williams, T. A., Cherlin, S., & Embley, T. M. (2020). Generalizing rate heterogeneity across sites in statistical phylogenetics. Statistical Modelling, 20(4), 410-436. https://doi.org/10.1177/1471082x18829937

Identifying the effect of public holidays on daily demand for gas (2020)
Journal Article
Heaps, S. E., Farrow, M., & Wilson, K. J. (2020). Identifying the effect of public holidays on daily demand for gas. Journal of the Royal Statistical Society: Series A, 183(2), 471-492. https://doi.org/10.1111/rssa.12504

Encapsulated Nanodroplet Crystallization of Organic-Soluble Small Molecules (2020)
Journal Article
Tyler, A. R., Ragbirsingh, R., McMonagle, C. J., Waddell, P. G., Heaps, S. E., Steed, J. W., …Probert, M. R. (2020). Encapsulated Nanodroplet Crystallization of Organic-Soluble Small Molecules. Chem, 6(7), 1755-1765. https://doi.org/10.1016/j.chempr.2020.04.009

Small molecules can form crystalline solids, in which individual molecules pack together into ordered three-dimensional arrays. Once a suitable crystal is grown, the packing and atomic connectivity of the constituent molecules can be studied by X-ray... Read More about Encapsulated Nanodroplet Crystallization of Organic-Soluble Small Molecules.

The Effect of Nonreversibility on Inferring Rooted Phylogenies (2017)
Journal Article
Cherlin, S., Heaps, S. E., Nye, T. M., Boys, R. J., Williams, T. A., & Embley, T. M. (2017). The Effect of Nonreversibility on Inferring Rooted Phylogenies. Molecular Biology and Evolution, 35(4), 984-1002. https://doi.org/10.1093/molbev/msx294

Integrative modeling of gene and genome evolution roots the archaeal tree of life (2017)
Journal Article
Williams, T. A., Szöllősi, G. J., Spang, A., Foster, P. G., Heaps, S. E., Boussau, B., …Embley, T. M. (2017). Integrative modeling of gene and genome evolution roots the archaeal tree of life. Proceedings of the National Academy of Sciences, 114(23), E4602-E4611. https://doi.org/10.1073/pnas.1618463114

Bayesian modelling of rainfall data by using non-homogeneous hidden Markov models and latent Gaussian variables (2015)
Journal Article
Heaps, S. E., Boys, R. J., & Farrow, M. (2015). Bayesian modelling of rainfall data by using non-homogeneous hidden Markov models and latent Gaussian variables. Journal of the Royal Statistical Society: Series C, 64(3), 543-568. https://doi.org/10.1111/rssc.12094

New substitution models for rooting phylogenetic trees (2015)
Journal Article
Williams, T. A., Heaps, S. E., Cherlin, S., Nye, T. M., Boys, R. J., & Embley, T. M. (2015). New substitution models for rooting phylogenetic trees. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1678), Article 20140336. https://doi.org/10.1098/rstb.2014.0336

Computation of marginal likelihoods with data-dependent support for latent variables (2014)
Journal Article
Heaps, S. E., Boys, R. J., & Farrow, M. (2014). Computation of marginal likelihoods with data-dependent support for latent variables. Computational Statistics & Data Analysis, 71, 392-401. https://doi.org/10.1016/j.csda.2013.07.033

Bayesian modelling of compositional heterogeneity in molecular phylogenetics (2014)
Journal Article
Heaps, S. E., Nye, T. M., Boys, R. J., Williams, T. A., & Embley, T. M. (2014). Bayesian modelling of compositional heterogeneity in molecular phylogenetics. Statistical Applications in Genetics and Molecular Biology, 13(5), 589-609. https://doi.org/10.1515/sagmb-2013-0077

An Introduction to Phylogenetics and the Tree of Life (2014)
Book Chapter
Williams, T. A., & Heaps, S. E. (2014). An Introduction to Phylogenetics and the Tree of Life. In M. Goodfellow, I. Sutcliffe, & J. Chun (Eds.), New Approaches to Prokaryotic Systematics (13-44). Academic Press. https://doi.org/10.1016/bs.mim.2014.05.001

Discussion of ''Modelling multivariate counts varying continuously in space'' by A. M. Schmidt and M. A. Rodriguez (2011)
Presentation / Conference Contribution
(2011). Discussion of ''Modelling multivariate counts varying continuously in space'' by A. M. Schmidt and M. A. Rodriguez. In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 9: Proceedings of the Ninth Valencia International Conference on Bayesian Statistics. https://doi.org/10.1093/acprof%3Aoso/9780199694587.001.0001