Lucy MorganPhD student, Associate Lecturer
Before coming to STOR-i I received a BSc in Mathematics from the University of Lancaster. During my undergraduate degree I looked at a wide variety of topics spreading both pure mathematics and statistics. Even before degree level mathematics I had an interest in statistics, environmental statistics in particular. This lead to me taking a minor course in environmental science in my first year alongside my mathematics degree. During the first year of university I heard about the STOR-i programme and followed its development throughout my degree. It was therefore delighted when I got the offer to take part in the summer internship 2013 to get an insight into research and get to know more about the programme. My project, Background Subtraction: Methods for Video Analysis, focused on surveillance and investigated the effectiveness of different algorithms for background subtraction under a number of real and challenging scenarios. My PhD project focuses on quantification of input uncertainty in simulation with current focus on arrival processes in queueing models. Input uncertainty arises when the inputs to simulation models can only be modelled by a finite amount of data and as such are not certain.
Detecting bias due to input modelling in computer simulation
Morgan, L., Nelson, B.L., Titman, A.C., Worthington, D.J. 3/12/2017 In: 2017 Winter Simulation Conference (WSC). Piscataway, NJ, USA : IEEE Press p. 1974-1985. 12 p. ISBN: 9781538634301. Electronic ISBN: 9781538634288.
The Importance of Input Uncertainty Quantification in Social Science Simulation
Onggo, B.S.S., Morgan, L. 25/09/2017
Input uncertainty quantification for simulation models with piecewise-constant non-stationary Poisson arrival processes
Morgan, L., Titman, A.C., Worthington, D.J., Nelson, B.L. 11/12/2016 In: WSC '16 Proceedings of the 2016 Winter Simulation Conference . Piscataway, NJ, USA : IEEE Press p. 370-381. 12 p. Electronic ISBN: 9781509044849.
- Statistical Methods in Medicine
- STOR-i Centre for Doctoral Training