Nick Heard is Chair in Statistics in the Department of Mathematics at Imperial College. His research interests center around computational Bayesian infererence, clustering and changepoint analysis, with a focus on application to large dynamic networks, such as computer networks or social networks, and bioinformatics problems.
Prof Nick Heard's personal web page can be found at http://stats.ma.ic.ac.uk/~naheard
Rubin-Delanchy P, Heard NA, Lawson D, 2019, Meta-analysis of mid-p-values: some new results based on the convex order, Journal of the American Statistical Association, Vol:114, ISSN:0162-1459, Pages:1105-1112
Bolton A, Heard N, 2018, Malware family discovery using reversible jump MCMC sampling of regimes, Journal of the American Statistical Association, Vol:113, ISSN:0162-1459, Pages:1490-1502
Heard N, Rubin-Delanchy P, 2018, Choosing between methods of combining p-values, Biometrika, Vol:105, ISSN:0006-3444, Pages:239-246
Heard NA, Turcotte MJM, 2016, Adaptive sequential Monte Carlo for multiple changepoint analysis, Journal of Computational and Graphical Statistics, Vol:26, ISSN:1537-2715, Pages:414-423