Contact Dr Trevor Ringrose
- Email: t.j.ringrose@cranfield.ac.uk
Background
PhD (1990) from Sheffield University in statistics applied to archaeology. Postdoctoral research at Reading University (1989-1922) and lectureship at Aberdeen University (1992-1997).
Current activities
Research in confidence regions for correspondence analysis. An R package performing standard correspondence analysis and showing confidence ellipses for chosen points can be downloaded from:
http://cran.r-project.org/web/packages/cabootcrs/index.html
Publications
Articles In Journals
- Cai Y, Pascoletti G, Zioupos P, Budair B, Zanetti EM, .... (2024). Parametrization of the Calcaneus and Medial Cuneiform to Aid Potential Advancements in Flatfoot Surgery. Life, 14(3)
- Smith J, Ringrose T & Barker S. (2024). An experimental intervention to investigate user perceptions of computer versus manual board wargame. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 21(2)
- Ringrose TJ. (2024). Alternative bootstrap confidence regions for multiple correspondence analysis. Communications in Statistics - Simulation and Computation, ahead-of-print(ahead-of-print)
- Stephens M, Errickson D, Giles SB & Ringrose TJ. (2021). Erratum to “Assessing the quality of footwear marks recovered from simulated graves” [Sci. Justice 60(6) (2020) 512–521]. Science & Justice, 61(1)
- Stephens M, Errickson D, Giles SB & Ringrose TJ. (2020). Assessing the quality of footwear marks recovered from simulated graves. Science & Justice, 60(6)
- Stevenson T, Carr DJ, Penn-Barwell JG, Ringrose TJ & Stapley SA. (2018). The burden of gunshot wounding of UK military personnel in Iraq and Afghanistan from 2003–14. Injury, 49(6)
- Fredericks JD, Ringrose TJ, Dicken A, Williams A & Bennett P. (2015). A potential new diagnostic tool to aid DNA analysis from heat compromised bone using colorimetry: A preliminary study. Science & Justice, 55(2)
- Ringrose T. (2013). Book Review: War Games: A History of War on Paper by Philipp von Hilgers. War in History, 20(3)
- Boutselis P & Ringrose TJ. (2013). GAMLSS and neural networks in combat simulation metamodelling: A case study. Expert Systems with Applications, 40(15)
- Ringrose TJ. (2012). Bootstrap confidence regions for correspondence analysis. Journal of Statistical Computation and Simulation, 82(10)
- Lombardo R & Ringrose T. (2012). Bootstrap confidence regions in non-symmetrical correspondence analysis. Electronic Journal of Applied Statistical Analysis, 5(3)
- Ringrose TJ. (2006). Neutral Umpires and Leg Before Wicket Decisions in Test Cricket. Journal of the Royal Statistical Society Series A: Statistics in Society, 169(4)
- Alam FM, McNaught KR & Ringrose TJ. (2006). An Artificial Neural Network Based Metamodel for Analysing a Stochastic Combat Simulation. International Journal of Enterprise Information Systems, 2(4)
- Ringrose TJ & Forth SA. (2005). Simplifying Multivariate Second-Order Response Surfaces by Fitting Constrained Models Using Automatic Differentiation. Technometrics, 47(3)
- Horsfall I, Watson C, Champion S, Prosser P & Ringrose T. (2005). The effect of knife handle shape on stabbing performance. Applied Ergonomics, 36(4)
- Alam FM, McNaught KR & Ringrose TJ. (2004). A comparison of experimental designs in the development of a neural network simulation metamodel. Simulation Modelling Practice and Theory, 12(7-8)
- Ketzscher R & Ringrose TJ. (2002). Exploratory analysis of European Professional Golf Association statistics. Journal of the Royal Statistical Society: Series D (The Statistician), 51(2)
- Benn DI & Ringrose TJ. (2001). Random variation of fabric eigenvalues: implications for the use of a‐axis fabric data to differentiate till facies. Earth Surface Processes and Landforms, 26(3)
- Latulippe C, Lapointe MF & Talbot T. (2001). Visual characterization technique for gravel-cobble river bed surface sediments; validation and environmental applications Contribution to the programme of CIRSA (Centre Interuniversitaire de Recherche sur le Saumon Atlantique). Earth Surface Processes and Landforms, 26(3)
- Benn DI & Ringrose TJ. (2001). Random variation of fabric eigenvalues: implications for the use of a-axis fabric data to differentiate till facies. Earth Surface Processes and Landforms, 26(3)
- Gilmour SG & Ringrose TJ. (1999). Controlling Processes in Food Technology by Simplifying the Canonical form of Fitted Response Surfaces. Journal of the Royal Statistical Society Series C: Applied Statistics, 48(1)
- CLEGG EJ, RINGROSE TJ & CROSS JF. (1998). SOME FACTORS AFFECTING MARITAL DISTANCES IN THE OUTER HEBRIDES. Journal of Biosocial Science, 30(1)
- Kerr NW & Ringrose TJ. (1998). Factors affecting the lifespan of the human dentition in Britain prior to the seventeenth century. British Dental Journal, 184(5)
- Ringrose TJ & Benn DI. (1997). Confidence regions for fabric shape diagrams. Journal of Structural Geology, 19(12)
- Ringrose T. (1996). Alternative confidence regions for canonical variate analysis. Biometrika, 83(3)
- Ringrose TJ. (1995). Response to Pilgram and Marshall “bone counts andstatisticians: A reply to Ringrose”. Journal of Archaeological Science, 22(1)
- Ringrose TJ. (1993). Bone Counts and Statistics: A Critique. Journal of Archaeological Science, 20(2)
- Ringrose TJ. (1992). Bootstrapping and correspondence analysis in archaeology. Journal of Archaeological Science, 19(6)
- Ringrose TJ & Krzanowski WJ. (1991). Simulation study of confidence regions for canonical variate analysis. Statistics and Computing, 1(1)
Conference Papers
- Horsfall I, Ringrose T, Watson C & Horsfall I. (2008). A statistical approach to proof testing
- Alam FM, McNaught KR & Ringrose TJ. (2004). Using Morris' Randomized Oat Design as a Factor Screening Method for Developing Simulation Metamodels
- Alam FM, McNaught KR & Ringrose TJ. (2004). Using morris' randomized oat design as a factor screening method for developing simulation metamodels
- Ringrose TJ, Alam MF & McNaught KR. (2002). Investigating Appropriate Experimental Designs for Neural Network Simulation Metamodels
- Ringrose T & Forth S. (2002). Improved Fitting of Constrained Multivariate Regression Models using Automatic Differentiation
