Jamie Scott

I am a PhD candidate in Statistics at Imperial College London, supervised by Professor Axel Gandy and funded by an EPSRC scholarship. Prior to the PhD, I received an MRes from UCL, an MSc in Statistics from Imperial and an MA from the University of Cambridge.

My current research involves developing methodology for inference in complex networks. See my research interests here.

526 Huxley Building
Department of Mathematics
Imperial College London, SW7 2AZ
james.scott15 "at" imperial.ac.uk

Research

Gandy A. and Scott J. (2020), "Unit Testing MCMC and Other Monte Carlo Methods,", arXiv:2001.06465 [stat.ME].

We propose approaches for testing implementations of Markov Chain Monte Carlo methods as well as of general Monte Carlo methods. Based on statistical hypothesis tests, these approaches can be used in a unit testing framework Read more

Scott J. and Gandy A. (2019), "State-Dependent Kernel Selection for Conditional Sampling of Graphs" Accepted for publication, Journal of Computational and Graphical Statistics

This paper introduces new efficient algorithms for two problems: sampling conditional on vertex degrees in unweighted graphs, and sampling conditional on vertex strengths in weighted graphs. The algorithms can sample conditional Read more