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Publications

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  2009 T. Joyce, O. Gaffney, S. Wilson and S. Kher Modeling and adapting production environmental stress testing Journal of the Institute of Environmental Science and Technology, 52(1), pp52-62. DOI: http://dx.doi.org/10.17764/jiet.52.1.q03j8khr5g4k58q4
  2012 Alicia Quirós Carretero and Simon P. Wilson Dependent Gaussian mixture models for source separation Journal on Advances in Signal Processing, 2012, pp239. DOI: http://dx.doi.org/10.1186/1687-6180-2012-239
  2011 Alicia Quirós Carretero and Simon P. Wilson Dependent Gaussian mixture models for source separation 19th European Signal Processing Conference. DOI: http://dx.doi.org/10.1186/1687-6180-2012-239
  2010 Alicia Quirós Carretero, Raquel Montes Diez and Simon P. Wilson Bayesian spatiotemporal model of fMRI data using transfer functions Neuroimage, 52(3), pp995-1004 . DOI: http://dx.doi.org/10.1016/j.neuroimage.2009.12.085
  2021 Antonio Pievatolo, Fabrizio Ruggeri, Refik Soyer and Simon Wilson Decisions in risk and reliability: an explanatory perspective Stats, 4(2), pp228-250. DOI: https://doi.org/10.3390/stats4020017
  2018 Arfianti T, Wilson S, Costello M.J Progress in the discovery of amphipod crustaceans PeerJ, 2018(7). DOI: http://dx.doi.org/10.7717/peerj.5187
  2011 Arnab Bhattacharya and Simon P. Wilson Inference for Discrete Latent Time Series Processes 58th Congress of the International Statistical Institute
  2010 Bahman Honari, John Donovan, Toby Joyce, Simon Wilson, Eamonn Murphy Stress test optimisation using an integrated production test and reliability field model Quality and Reliability Engineering International, 26(6), pp579-592. DOI: http://dx.doi.org/10.1002/qre.1081
  2005 Bannister, R. Gregg, D. Wilson, S. Nisbet, A. FPGA implementation of an Image Segmentation algorithm using logarithmic arithmetic Midwest Symposium on Circuits and Systems, 2005, pp810-813 . DOI: http://dx.doi.org/10.1109/MWSCAS.2005.1594224
  2009 Ben Flood, Brett Houlding, Simon P. Wilson, Sergiy Vilkomir. A probability model of system downtime with implications for optimal warranty design Quality and Reliability Engineering International, 26(1), pp 83 - 96. DOI: http://dx.doi.org/10.1002/qre.1049
  2018 Bhattacharya A, Wilson S.P Sequential Bayesian inference for static parameters in dynamic state space models Computational Statistics and Data Analysis, 127, pp187-203. DOI: http://dx.doi.org/10.1016/j.csda.2018.05.018
  2019 Bhattacharya A, Wilson S.P, Soyer R A Bayesian approach to modeling mortgage default and prepayment European Journal of Operational Research, 274(3), pp1112-1124. DOI: http://dx.doi.org/10.1016/j.ejor.2018.10.047
  2015 Bhattacharya, A. and Wilson, S. Sequential Bayesian Inference for Dynamic State Space Model Parameters Current Trends in Bayesian Methodology with Applications, pp123-134. DOI: http://dx.doi.org/10.1201/b18502-13
  2011 Brett Houlding and Simon P. Wilson Considerations on the UK re-arrest hazard rate analysis Journal of Law, Probability and Risk, 10(4), pp303-328. DOI: http://dx.doi.org/10.1093/lpr/mgr015
  2011 Brett Houlding and Simon P. Wilson Considerations on the UK Re-Arrest Hazard Data Analysis (How Model Selection Can Alter Conclusions for Policy Development) 58th Congress of the International Statistical Institute
  2021 Cahill, J., Cullen P, Anwer S, Wilson, S & Gaynor K. Pilot Work Related Stress (WRS), Effects on Wellbeing (Including Mental Health) & Coping Methods The International Journal of Aerospace Psychology. DOI: http://dx.doi.org/10.1080/24721840.2020.1858714
  2020 Cahill, J.; Cullen, P.; Anwer, S.; Gaynor, K.; Wilson, S. The Requirements for New Tools for Use by Pilots and the Aviation Industry to Manage Risks Pertaining to Work-Related Stress (WRS) and Wellbeing, and the Ensuing Impact on Performance and Safety Technologies, 8(3), pp1-49. DOI: https://doi.org/10.3390/technologies8030040
  1998 Cathal Walsh, Simon Wilson RELIABILITY MODELLING AND INFERENCE THROUGH FATIGUE CRACK GROWTH Series on quality, reliability and engineering statistics, pp397-410. DOI: https://doi.org/10.1142/9789812816580_0029
  2021 Chaitanya Joshi, Fabrizio Ruggeri and Simon Wilson Bayesian implementation of the fault tree analysis Wiley StatsRef: Statistics Reference Online
  2014 Coolen, F.P.A., Aslett, L. and Wilson, S.P. Bayesian inference for reliability of systems and networks using the survival signature Risk Analysis. DOI: http://dx.doi.org/10.1111/risa.12228
  2015 Costello M.J, Lane M, Wilson S, Houlding B Factors influencing when species are first named and estimating global species richness Global Ecology and Conservation, 4, pp243-254. DOI: http://dx.doi.org/10.1016/j.gecco.2015.07.001
  2014 Costello MJ, Houlding B, Wilson SP As in other taxa, relatively fewer beetles are being described by an increasing number of authors: response to Löbl and Leschen Systematic Entomology, 39(3), pp395–399. DOI: http://dx.doi.org/10.1111/syen.12068
  2013 Costello, M.J., Wilson, S., Houlding, B. More taxonomists describing significantly fewer species per unit effort may indicate that most species have been discovered Systematic Biology, 62(4), pp616-624. DOI: http://dx.doi.org/10.1093/sysbio/syt024
  2025 Cristina De Persis, José Luis Bosque, Irene Huertas, M. Remedios Sillero¿Denamiel, Simon Wilson Quantitative System Risk Assessment From Incomplete Data With Belief Networks and Pairwise Comparison Elicitation Risk Analysis, 45(11), pp4014-4038. DOI: https://doi.org/10.1111/risa.70114
  2024 Cunningham, J.A. and Padamsee, M. and Wilson, S. and Costello, M.J. Fungi species description rates confirm high global diversity and suggest half remain unnamed Frontiers of Biogeography, 16(2). DOI: http://dx.doi.org/10.21425/F5FBG62358
  2015 De Persis C, Wilson S IAC-15-A6.2.11 A risk assessment tool for highly energetic break-up events during the atmospheric re-entry , 3, pp2059-2066
  2016 De Persis, C. and Wilson, S. Using the analytic hierarchy process in the assessment of the probability for an explosion to occur during the atmospheric re-entry Proceedings of the International Astronautical Congress, IAC
  2002 Dina Melas and Simon P. Wilson Double Markov random fields and Bayesian image segmentation IEEE Transactions on Signal Processing, 50(2), pp357-365. DOI: http://dx.doi.org/10.1109/78.978390
  2007 F. Ruggeri, R. Kennett and F. Faltin Encyclopedia of Statistics in Quality and Reliability
  2023 Hartebrodt, L. and Wilson, S. and Costello, M.J. Progress in the discovery of isopods (Crustacea: Peracarida)—is the description rate slowing down? PeerJ, 9. DOI: http://dx.doi.org/10.7717/peerj.15984
  2010 Honari, B. and Donovan, J. and Joyce, T. and Wilson, S. and Murphy, E. Stress test optimization using an integrated production test and field reliability model Quality and Reliability Engineering International, 26(6), pp579-592. DOI: http://dx.doi.org/10.1002/qre.1081
  2008 Honari, B., Donovan, J., Joyce, T., Wilson, S. Application of generalized linear models for optimizing production stress testing 2008 Annual Reliability and Maintainability Symposium. DOI: http://dx.doi.org/10.1109/RAMS.2008.4925806
  2020 Insua D.R, Ruggeri F, Soyer R, Wilson S Advances in Bayesian decision making in reliability European Journal of Operational Research, 282, pp1-18. DOI: http://dx.doi.org/10.1016/j.ejor.2019.03.018
  1997 J. Eliashberg, Nozer D. Singpurwalla and Simon P. Wilson Calculating the reserve for a time and usage indexed warranty Management Science, 43(7), pp966-975. DOI: http://dx.doi.org/10.1287/mnsc.43.7.966
  2006 J. Haslett, M. Whiley, S. Bhattacharya, M. Salter-Townshend, J.R.M. Allen, B. Huntley, F.J.G. Mitchell and S.P. Wilson Bayesian palaeoclimate reconstruction Journal of the Royal Statistical Society, Series A, 169(3), pp395-438. DOI: http://dx.doi.org/10.1111/j.1467-985X.2006.00429.x
  2018 Joan Cahill, Una Geary, Ewan Douglas, Simon Wilson, Michael Ferreira, Brian Gilbert User and design requirements and production of evidence: using incident analysis data to (1) inform user scenarios and bow ties, and (2) generate user and design requirements Cognition, Technology & Work, 20(1), pp23--47
  2006 John Haslett, Sourabh Bhattacharya, Matt Whiley, Michael Salter-Townshend, Simon P. Wilson, J.R.M. Allen and B. Huntley, F.J.G. Mitchell Bayesian Palaeoclimate Reconstruction Journal of the Royal Statistical Society, Series A, 169(3), pp1-36
  2018 Joshi, C. and Ruggeri, F. and Wilson, S.P. Prior Robustness for Bayesian Implementation of the Fault Tree Analysis IEEE Transactions on Reliability, 67(1), pp170-183. DOI: http://dx.doi.org/10.1109/TR.2017.2778241
  2011 Katarina Domijan and Simon P Wilson Bayesian kernel projections for classification of high dimensional data Statistics and Computing, 21(2), pp203-. DOI: http://dx.doi.org/10.1007/s11222-009-9161-8
  2001 Kevin McDaid and Simon P. Wilson Deciding how long to test software The Statistician, 50(2), pp117-134. DOI: http://dx.doi.org/10.1111/1467-9884.00265
  2010 Louis J. M. Aslett, Simon Wilson Modelling and Inference for Networks with Repairable Redundant Subsystems
  2011 Louis J.M. Aslett and Simon P. Wilson Markov Chain Monte Carlo for Inference on Phase-Type Models 58th Congress of the International Statistical Institute
  2011 M. Costello & Simon P. Wilson Predicting the number of known and unknown species in European seas using rates of description Global Ecology and Biogeography, 20(2), pp319-330. DOI: http://dx.doi.org/10.1111/j.1466-8238.2010.00603.x
  2020 M. Pages, P. Bock, D. Gordon, C. Linares, B. Hereu, S.P. Wilson and M. Costello Progress in the discovery of extant and fossil Bryozoans Marine Ecology Progress Series, 635, pp71-79. DOI: http://dx.doi.org/10.3354.meps13201
  2014 Mai, T. and Ghosh, B. and Wilson, S. Short-term traffic-flow forecasting with auto-regressive moving average models Proceedings of the Institution of Civil Engineers: Transport, 167(4), pp232-239. DOI: http://dx.doi.org/10.1680/tran.12.00012
  2013 Mai, T., Ghosh, B., Wilson, S. Short-term traffic flow forecasting with A-SVARMA Proceedings of the Institution of Civil Engineering-Transport, 167(4), pp232-239
  2012 Mark Costello, Simon P. Wilson and Brett Houlding Predicting total global species richness using rates of species description and estimates of taxonomic effort Systematic Biology, 61(5), pp871-883. DOI: http://dx.doi.org/10.1093/sysbio/syr080
  2021 Markus Rao, Rachel Mandelbaum, S. Schmidt and Y. Mao A composite likelihood approach for inference under photometric redshift uncertainty Monthly Notices of the Royal Astronomical Society. DOI: https://doi.org/10.1093/mnras/stab3290
  2019 Markus Rau, Rachel Mandelbaum and Simon Wilson Estimating redshift distributions using Hierarchical Logistic Gaussian processes Monthly Notices of the Royal Astronomical Society. DOI: http://dx.doi.org/10.1093/mnras/stz3295
  2004 Matt Whiley and Simon P. Wilson Parallel algorithms for Markov chain Monte Carlo methods in latent spatial Gaussian models Statistics and Computing, 14(3), pp171-179. DOI: http://dx.doi.org/10.1023/B:STCO.0000035299.51541.5e

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