Research 
mvstat.net
Home
  Contact   Research   Software   CV
 

Research interests
  • Kernel smoothing
  • Non-parametric statistics
  • Statistical software
  • Statistical applications for biological data
Refereed publications
  1. Chacón, J.E., Duong, T. (2014) Efficient recursive algorithms for functionals based on higher order derivatives of the multivariate Gaussian density. Statistics and Computing DOI: 10.1007/s11222-014-9465-1. R script file.
  2. Pyne, S., Lee, S.X., Irish, J., Tamayo, P., Nazaire, M.-D., Duong, T. >, Ng, S.-K., Hafler, D., Levy, R., Nolan, G.P., Mesirov, J. and McLachlan, G.J . (2014) Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data. PLoS ONE 9, e100334.
  3. Schauer, K., Grossier, J.-P., Duong, T., Chapuis, V., Degot, S., Lescure, A., Del Nery, E., and Goud, B. (2014) A novel organelle map framework for high-content cell morphology analysis in high throughput. Journal of Biomolecular Screening 19, 317 - 324.
  4. Schauer, K., Duong, T., Gomes-Santos, C. S. and Goud, B. (2013) Studying intracellular trafficking pathways with probabilistic density maps. Cell Methods in Biology 118, 326 - 343.
  5. Duong, T. (2013) Local significant differences from nonparametric two-sample tests. Journal of Nonparametric Statistics 25, 635 - 645.
  6. Chacón, J.E., Duong, T. (2013) Data-driven density estimation, with applications to nonparametric clustering and bump hunting. Electronic Journal of Statistics 7, 499 - 532.
  7. Duong, T., Goud, B. and Schauer, K. (2012) First closed-form density based framework for automatic detection for cellular morphology changes. Proceedings of the National Academy of Sciences 109, 8382 - 8387.
  8. Chacón, J.E., Duong, T. (2011) Unconstrained pilot selectors for smoothed cross validation. Australian & New Zealand Journal of Statistics 53, 331 - 351.
  9. Chacón, J.E., Duong, T. and Wand, M.P (2011). Asymptotics for general multivariate kernel density derivative estimators. Statistica Sinica 21, 807 - 840.
  10. Lasserre, R., Charrin, S., Cuche, C., Danckaert, A., Thoulouze, M.-I., de Chaumont, F., Duong, T., Perrault, N., Varin-Blank, N., Olivo-Marin, J.-C., Etienne-Manneville, S., Arpin, M., Di Bartolo, V. and Alcover, A. (2010). Ezrin tunes T cell activation by controlling Dlg1 and microtubule positioning at the immunological synapse. EMBO Journal 29, 2301 - 2314.
  11. Schauer, K., Duong, T., Bleakley, K., Bardin, S., Bornens, M. and Goud, B. (2010). Probabilistic density maps to study global endomembrane organization. Nature Methods 7, 560 - 567.
  12. Chacón, J.E. and Duong, T. (2010). Multivariate plug-in bandwidth selection with unconstrained pilot bandwidth matrices. Test 19, 375 - 398.
  13. Thérizols, P., Duong, T., Dujon, B., Fabre, E. and Zimmer, C. (2010) Chromosome arm length and nuclear constraints determine the dynamic relationship of yeast subtelomeres. Proceedings of the National Academy of Sciences 107, 2025 - 2030.
  14. Duong, T., Koch, I. and Wand, M.P. (2009) Highest density difference region estimation with application to flow cytometric data. Biometrical Journal 3, 504 - 521.
  15. Berger, A.B., Cabal, G.G., Fabre, E., Duong, T., Buc, H., Nehrbass, U., Olivo-Marin, J.-C., Gadal, O. and Zimmer, C. (2008) High-resolution statistical mapping reveals gene territories in live yeast. Nature Methods 5, 1031 - 1037.
  16. Duong, T., Cowling, A., Koch, I. and Wand, M.P. (2008) Feature significance for multivariate kernel density estimation. Computational Statistics and Data Analysis 52, 4225 - 4242.
  17. Duong, T. (2007) ks: Kernel density estimation and kernel discriminant analysis for multivariate data in R. Journal of Statistical Software 21(7), 1 - 16.
  18. Duong, T. and Hazelton, M.L. (2005). Cross-validation bandwidth matrices for multivariate kernel density estimation. Scandinavian Journal of Statistics 32, 485 - 506.
  19. Duong, T. and Hazelton, M.L. (2005) Convergence rates for unconstrained bandwidth matrix selectors in multivariate kernel density estimation. Journal of Multivariate Analysis 93, 417 - 433.
  20. Duong, T. and Hazelton, M.L. (2003) Plug-in bandwidth selectors for bivariate kernel density estimation. Journal of Nonparametric Statistics 15, 17 - 30.
Other publications
  1. Duong, T., Cowling, A., Koch, I. and Wand, M.P. (2006) Feature significance for multivariate data and kernel density estimation. Proceedings of the 8th Workshop on Nonparametric Statistical Analysis and Related Areas, Keio University, Tokyo, 27-28 March 2006, 34 - 42.
  2. Duong, T. (2005) Bandwidth selectors for multivariate kernel density estimation. Bulletin of the Australian Mathematical Society 71, 351 - 352.
  3. Duong, T. (2004) Bandwidth selectors for multivariate kernel density estimation. PhD thesis. University of Western Australia, Australia. Errata.
  4. Duong, T. and Hazelton, M.L. (2001) Efficient day-to-day simulation of traffic systems with applications to pre-trip information in Proceedings of the 8th World Congress on Intelligent Transport Systems [CD-ROM].
Seminars
  1. Interaction of abstract and concrete questions for kernel estimators. Theoretical and Applied Statistics Laboratory (LSTA), University Pierre and Marie Curie - Paris 6, Paris, France, 27 Nov 2012.
  2. Quantitative statistical analysis of biological experimental data. Institut Curie, Paris, France, Mar 2010.
  3. Statistical reconstruction of yeast nuclear organisation. Institut Pasteur, Paris, France, Oct 2008.
  4. A tour of kernel smoothing. Institut Pasteur, Paris, France, Oct 2007.
  5. Estimating highest density difference regions using generalised chi-squared tests. Fred Hutchinson Cancer Research Center, Seattle, USA. Nov 2006.
  6. Convergence rates for unconstrained bandwidth matrix selectors in multivariate kernel density estimation. University of Sydney, Sydney, Australia. Aug 2006.
  7. Feature significance for multivariate kernel density estimation.
    • Massey University, Palmerston North, New Zealand, July 2006.
    • Australian Statistics Conference/ New Zealand Statistical Association Conference, Auckland, New Zealand, July 2006.
    • University of New South Wales, Sydney, Australia, May 2006.
  8. Software for multivariate kernel smoothing University of New South Wales, Sydney, Australia, Sept 2005.
  9. Bandwidth selectors for multivariate kernel density estimation
    • Macquarie University, Sydney, Australia, Mar 2005.
    • Université Laval, Québec, Canada, Aug 2004.
    • Université de Montréal, Montréal, Canada, Aug 2004.
  10. Applications of bivariate kernel density estimators Macquarie University, Sydney, Australia, Dec 2003.
  11. Plug-in bandwidth selectors for bivariate kernel density estimation
    • University of Western Australia, Australia, May 2002
    • International Conference on Current Advances and Trends in Non-parametric Statistics, Crete, Greece, July 2002
    • Oxford University, United Kingdon, May 2003.
  12. Efficient day-to-day simulation of traffic systems with applications to pre-trip information, 8th World Congress on Intelligent Transport Systems, Sydney, Australia, Oct 2001.
  13. An introduction to kernel density estimation, University of Western Australia, Australia, May 2001.
  14. Testing food-intake hypotheses using the ABS National Nutrition Survey. Workshop on Sample Surveys and Social and Economic Statistics, University of Wollongong, Wollongong, Australia, June 2000.
Web documents
  1. R vignette: ks: Kernel density estimation for bivariate data
  2. R vignette: feature: an R package for feature significance for multivariate kernel density estimation
  3. R vignette: Using prim for bump hunting
  4. R vignette: Using prim to estimate highest density differnce regions
  5. Wikipedia page: Multivariate kernel density estimation
Bibliometry
  1. Google Scholar
  2. Scopus (preview)