Homepage of Owen Jones
Teaching
Semester 2
Research Interests
Stochastic modelling, in particular in forest hydrology
Construction and estimation of selfsimilar and fractal processes
Stochastic optimisation
Selected Publications
Books
Papers
 Decrouez, G., Hambly, B. and Jones, O.D., The Hausdorff spectrum of a class of multifractal processes. Stochastic Processes and their Applications, 2015. Preprint version
 Owen D Jones, Petter Nyman and Gary J Sheridan. Modelling the effects of fire and rainfall regimes on extreme erosion events in forested landscapes. Stochastic Environmental Research and Risk Assessment, 2014.
 David Rolls and Owen D Jones, An improved test for continuous local martingales. Communications in Statistics – Theory and Methods, 2014.
 F. Eng, HS. Gan, O. Jones, The Role of Communication in Emergency Evacuations: An Analysis of a Ring Network with a Static Disruption. Proceedings of the 17th International
IEEE Conference on Intelligent Transportation Systems, Qingdao, China, October 8–11 2014.
 A.W. Kowalewski, O.D. Jones, K. Ramamohanarao. Volatility homogenisation kernel for forecasting. Proceedings of the International workconference on Time Series (ITISE), Grenada, Spain June 25–27 2014, pp. 291–302.
 A.W. Kowalewski, O.D. Jones, K. Ramamohanarao. Volatility homogenisation decomposition for forecasting. Proceedings of IEEE Computational Intelligence for Financial Engineering and Economics, London, U.K., March 27–28 2014, pp. 182–189.
 S. Appalasamy, H.S. Gan, O.D. Jones, N.H. Moin, C.S. Tan. Transmission loss modelling and analysis with multiple linear regression. MODSIM 2013.
 Geoffrey Decrouez, PierreOlivier Amblard, Owen Jones. Estimation of the multifractal spectrum using the crossing tree. Gretsi 2013.
 Gary J. Sheridan, Philip J. Noske, Patrick N.J. Lane, Owen D. Jones and Christopher B. Sherwin. A simple two parameter model for scaling hillslope surface runoff. Earth Surface Processes and Landforms, 2013.
 Jones, O.D., Sheridan, G.J. and Lane P.J. Using queuing theory to describe steadystate runoffrunon phenomena and connectivity under spatially variable conditions. Water Resources Research, 2013.
 Decrouez, G. and Jones, O.D., A class of multifractal processes constructed using an embedded branching process. The Annals of Applied Probability, Vol. 22, No. 6, pp. 2357–2387,
2012.
DOI Full text
 O.D. Jones, P. Nyman and G.J. Sheridan,
A stochastic coverage model for erosion events caused by the intersection of burnt forest and convective thunderstorms
Proceedings MODSIM2011, pp. 23382344, 2011.
Full text
 Jones, O.D. and Rolls, D.A.,
A characterisation of, and hypothesis test for, continuous local martingales.
Electronic Comm. Prob. 16, pp. 638651, 2011.
Full text
 Biggins, J.D., Hambly, B.M. and Jones, O.D.,
Multifractal spectra for random selfsimilar measures via branching processes.
Adv. Appl. Prob., 43, pp. 139, 2011.
Preprint version
 Jones, O.D., Sheridan, G.J. and Lane, P.N.J.,
A stochastic runoff model incorporating spatial variability.
Proceedings 18th World IMACS Congress/MODSIM09, pp. 18651871, 2009.
Full text
 Decrouez, G., Amblard, PO., Brossier, JM and Jones, O.D.,
GaltonWatson iterated function systems.
J. Phys. A: Math. Theor., 42, pp. 095101095117, 2009.
DOI
Preprint version
 Davey, A.J.H., Doncaster, C.P. and Jones, O.D.,
Distinguishing between interference and exploitation competition for shelter in a mobile fish population.
Environmental Modelling and Assessment, 14, pp. 555562, 2009.
DOI
Preprint version and data
 Zaeem Burq and Owen Jones, Simulation of Brownian motion at first passage times.
Mathematics and Computers in Simulation, 77, pp. 6471, 2008.
DOI
Preprint version.
 Andre Costa, Owen Jones and Dirk Kroese. Convergence Properties of the CrossEntropy Method for Discrete Optimization.
Operations Research Letters, 35, pp. 573580, 2007.
DOI
Preprint version.
 Owen Jones, Modelling Electricity Power Cuts in the UK.
ANZIAM J., 47 (EMAC2005), pp. C585C602, 2007.
Full text.
 Johnnie Johnson, Owen Jones and Leilei Tang,
Exploring decision makers' use of price information in a speculative market.
Management Science, vol. 52, pp. 897907, 2006.
Abstract.
 Russell Cheng and Owen Jones,
Analysis of distributions in factorial experiments.
Statistica Sinica, 14, pp 10851103, 2004.
Abstract.
 Owen Jones,
Large deviations for supercritical multitype branching processes.
J. Appl. Probab, 41, pp 703720, 2004.
Abstract.
 Owen Jones,
Fast, efficient online simulation of selfsimilar processes.
In Thinking in Patterns: Fractals and Related Phenomena in Nature, M.M. Novak Ed., pp 165176, World Scientific 2004.
Abstract and corrected version.
 Owen Jones and Yuan Shen,
Estimating the Hurst index of a selfsimilar process via the crossing tree.
Signal Processing Letters, 11, pp 416419, 2004.
Abstract.
 Ben Hambly and Owen Jones,
Thick and thin points for random recursive fractals.
Adv. Appl. Prob., 35(2003), 251277.
Abstract.
 Ben Hambly and Owen Jones,
Asymptotically onedimensional diffusion on the Sierpinski gasket and multitype branching processes with varying environment.
J. Theoret. Prob., 15(2002), 285322.
Abstract.
 Owen Jones, Ted White and Bronwen Butler,
Estimating crystal growth rates using computed tomography.
Inverse Problems, 16(2000), 14771485.
Abstract.
 Owen Jones,
On the convergence of multitype branching processes with varying environments.
Ann. Appl. Prob., 7(1997), 772801.
Full text (postscript) and
errata (postscript).
 Owen Jones,
Transition probabilities for the simple random walk on the Sierpinski graph.
Stoc. Proc. Appl., 61(1996), 4569.
Abstract.
Software
Individuals are free to use this code for the purpose academic research, provided it is properly acknowledged. For any other use, permission must first be arranged with the author(s).
Simulating Brownian motion at first passage times
Matlab and R code for simulating Brownian motion as it first crosses points in delta*Z. A description of the algorithm is given in the paper "Simulation of Brownian motion at firstpassage times".
Estimation of the Hurst index
Matlab code for estimating the Hurst index H of a selfsimilar process. Details of the algorithm are available in the paper "Estimating the Hurst index of a selfsimilar process via the crossing tree".
Embedded Branching Process (EBP) selfsimilar processes
Matlab code for simulating EBP selfsimilar processes. Details of the algorithm are available in the paper "Fast, efficient online simulation of selfsimilar processes".
MultifractalEBP processes
Matlab code for simulating MultifractalEBP (MEBP) processes.
MEBP processes are a generalisation of EBP processes, which incorporate a multifractal timechange defined using a cascade process on the crossing tree.
 MEBP.m an easy to use front end
 MEBPsim.m a more flexible front end (saves a process state which allows later simulation of additional points)
 MEBPincr.m used by MEBPsim
 MEBPexpd.m used by MEBPsim
 MEBPinit.m used to generate initial state
Other InformationSome links to (work related) places I'm fond of:
