Publications of Hongquan Xu     (google scholar page)
All publications
  1. Wang, G., Zhu, K., Ye, J., Xu, H. and Liang, P. (1996). Seafloor nodules image recognition system. Geological Review 42, 560--563 (in Chinese).
  2. Xu, H. and Shen, S. (1998). Uniform designs based on computer experiments. Applied Mathematics: A Journal of Chinese Universities Series A 13, 167--174 (in Chinese).
  3. Shen, S. and Xu, H. (1998). Information criterion in experimental design. Bulletin of the Hong Kong Mathematical Society 2, 65--73.
  4. Xu, H. (1999). Universally optimal designs for computer experiments. Statistica Sinica, 9, 1083-1088.
  5. Xu, H. and Wu, C. F. J. (2001). Generalized minimum aberration for asymmetrical fractional factorial designsAnnals of Statistics, 29, 1066-1077.
  6. Xu, H., Wu, P., Wu, C. F. J., Tidwell, C. and Wang, Y. (2002). A smooth response surface algorithm for constructing gene regulatory network. Physiological Genomics, 11, 11-20.  US patent no. 60/297299.  
  7. Xu, H. (2002). An algorithm for constructing orthogonal and nearly-orthogonal arrays with mixed levels and small runs.  Technometrics, 44, 356-368. (C source code ) (S source code )  
  8. Xu, H. (2003). Minimum moment aberration for nonregular designs and supersaturated designsStatistica Sinica, 13, 691-708.
  9. Deng, L. Y. and  Xu, H. (2003). A System of High-dimensional, Efficient, Long-cycle and  Portable Uniform Random Number Generators.   ACM Transactions on Modeling and Computer Simulation, 13, 299-309.  [Online supplement
  10. Xu, H., Cheng, S.W. and Wu, C. F. J. (2004). Optimal Projective Three-Level Designs for Factor Screening and Interaction Detection. Technometrics, 46,  280-292.
  11. Xu, H. and Deng, L. Y. (2005). Moment Aberration Projection for Nonregular Fractional Factorial Designs.  Technometrics, 47, 121-131.
  12. Xu, H. (2005a). Some Nonregular Designs From the Nordstrom and Robinson Code and Their Statistical Properties.  Biometrika, 92, 385-397.  [pdf file]
  13. Xu, H. (2005b). A catalogue of three-level regular fractional factorial designs.  Metrika, 62, 259-281.  [online supplement]. 
  14. Xu, H. and Wu, C. F. J. (2005). Construction of Optimal Multi-Level Supersaturated DesignsAnnals of Statistics, 33, 2811-2836. [Online supplement and Xu and Wu (2003) UCLA Statistics Electronic Publications preprint 356]
  15. Xu, H. and Lau, S. (2006). Minimum Aberration Blocking Schemes for Two- and Three-Level Fractional Factorial Designs.   Journal of Statistical Planning and Inference, 136, 4088-4118.
  16. Xu, H. (2006). Blocked Regular Fractional Factorial Designs With Minimum Aberration.   Annals of Statistics, 34, 2534-2553.
  17. Shen, Q. and Xu, H.  (2007).  Diagnostics for Linear Models With Functional ResponsesTechnometrics, 49, 26-33.
  18. Yang, X., Shen, Q.,  Xu, H.  and Shoptaw, S. (2007).  Functional Regression Analysis using an F Test for Longitudinal Data with Large Numbers of Repeated Measures.  Statistics in Medicine, 26, 1552-1566. 
  19. Xu, H. and Wong, A. (2007).  Two-Level Nonregular Designs From Quaternary Linear CodesStatistica Sinica,  17, 1191-1213.
  20. Xu, H. and Cheng, C. -S. (2008).  A Complementary Design Theory for DoublingAnnals of Statistics, 36, 445-457.
  21. Xu, H. (2009). Algorithmic Construction of Efficient Fractional Factorial Designs With Large Run SizesTechnometrics, 51, 262-277.
  22. Phoa, F. K. H. and Xu, H. (2009). Quarter-Fraction Factorial Designs Constructed via Quaternary CodesAnnals of Statistics, 37, No. 5A, 2561-2581.
  23. Phoa, F. K. H.,  Pan, Y.-H. and Xu, H. (2009).  Analysis of Supersaturated Designs via the Dantzig Selector.   Journal of Statistical Planning and Inference, 139, 2362-2372. [Preprint]
  24. Xu, H., Phoa, F. K. H. and Wong, W. K. (2009). Recent Developments in Nonregular Fractional Factorial Designs. Statistics Surveys, 3, 18-46. DOI: 10.1214/08-SS040.
  25. Phoa, F. K. H., Xu, H. and Wong, W. K. (2009). The use of nonregular fractional factorial designs in combination toxicity studies. Food and Chemical Toxicology, 47, 2183-2188. [Preprint]
  26. Phoa, F. K. H., Wong, W. K. and Xu, H. (2009). The Need of Considering the Interactions in the Analysis of Screening Designs. Journal of Chemometrics, 23, 545-553. [Preprint]
  27. Xu, H., and Mee, R. W. (2010).  Minimum Aberration Blocking Schemes for 128-Run DesignsJournal of Statistical Planning and Inference,  140,  3213-3229.  [Preprint]
  28. Zhang, R., Phoa, F. K. H., Mukerjee, R. and Xu, H. (2011).  A Trigonometric Approach to Quaternary Code Designs with Application to One-Eighth and One-Sixteenth Fractions. Annals of Statistics, 39, No. 2, 931-955.
  29. Xu, H., Shen, Q., Yang, X. and Shoptaw, S. (2011).  A Quasi F Test for Functional Linear Models With Functional Covariates and its Application to Longitudinal Data. Statistics in Medicine, 26, 1552-1566. 
  30. Phoa, F. K. H., Mukerjee, R. and Xu, H. (2012). One-Eighth- and One-Sixteenth-Fraction Quaternary Code Designs With High Resolution. Journal of Statistical Planning and Inference, 142, 1073-1080.
  31. Chen, H.-W., Wong, W. K. and Xu, H.  (2012). An Augmented Approach to the Desirability Function. Journal of Applied Statistics,  39, 599-613.  DOI:10.1080/02664763.2011.605437
  32. Tang Y., Xu H. and Lin D. K. J. (2012).  Uniform fractional factorial designs. Annals of Statistics, 40, 891-907.
  33. Jaynes, J., Ding, X., Xu, H., Wong, W. K., and Ho, C.-M. (2013).  Application of Fractional Factorial Designs to Study Drug Combinations. Statistics in Medicine, 32, 307--318.  doi:10.1002/sim.5526
  34. Ding, X.,  Xu, H., Hopper, C.,  Yang, J. and Ho, C.-M. (2013). Use of fractional factorial designs in antiviral drug studies. Quality and Reliability Engineering International, 29, 299--304.  DOI:10.1002/qre.1308
  35. Chen, H.-W., Xu, H., and Wong, W. K. (2013). Balancing Location and Dispersion Effects for Multiple Responses. Quality and Reliability Engineering International,  29, 607-615.  DOI:10.1002/qre.1411
  36. Tang, Y. and Xu H.  (2013). An effective construction method for multi-level uniform designs. Journal of Statistical Planning and Inference,  143, 1583-1589.  DOI: 10.1016/j.jspi.2013.04.009
  37. Xu, H., Jaynes, J., and Ding, X. (2014). Combining Two-Level and Three-Level Orthogonal Arrays for Factor Screening and Response Surface Exploration. Statistica Sinica, 24,  269-289. doi:10.5705/ss.2012.210
  38. Tang, Y. and Xu, H.  (2014). Permuting Regular Fractional Factorial Designs for Screening Quantitative Factors. Biometrika, 101, 333-350.
  39. Zhou, Y. D. and Xu H.  (2014). Space-filling fractional factorial designs. Journal of the American Statistical Association, 109, 1134-1144.
  40. Gromping, U. and Xu, H. (2014). Generalized resolution for orthogonal arrays. Annals of Statistics, 42, 918-939.
  41. Ning, S., Xu, H., Al-Shyoukh, I., Feng, J., and Sun, R. (2014). An Application of a Hill-based Response Surface Model for a Drug Combination Experiment on Lung Cancer. Statistics in Medicine, 33, 4227-4236.
  42. Ding, X., Liu, W., Weiss, A., Li, Y., Wong, I.,  Griffioen, A., van den Bergh, H., Xu, H.,  Nowak-Sliwinska, P. and Ho, C.-M. (2014). Discovery of a low order drug-cell response surface for applications in personalized medicine. Physical Biology, 11, 065003. doi:10.1088/1478-3975/11/6/065003.
  43. Zhou, Y.  and Xu, H.  (2015). Space-filling properties of good lattice point sets. Biometrika, 102 (4), 959-966doi:10.1093/biomet/asv044.
  44. Chen, H.-W., Wong, W. K. and Xu, H.  (2016). Data-driven desirability function to measure patientsí disease progression in a longitudinal study. Journal of Applied Statistics, 43, 783-795.  doi:10.1080/02664763.2015.1077378.
  45. Jaynes, J., Wong, W. K. and Xu, H. (2016).  Using Blocked Fractional Factorial Designs to Construct Discrete Choice Experiments for HealthCare Studies. Statistics in Medicine, 35, 2543-2560.  doi: 10.1002/sim.6882.
  46. Jaynes, J., Zhao, Y.,  Xu, H., and Ho, C.-M. (2016). Use of Orthogonal Array Composite Designs to Study Lipid Accumulation in a Cell-Free System. Quality and Reliability Engineering International,  32, 1965-1974. doi: 10.1002/qre.1900.
  47. Jaynes, J., Xu, H. and Wong, W. K. (2017). Minimum Aberration Designs for Discrete Choice Experiments. Journal of Statistical Theory and Practice, 11, 339-360. doi: 10.1080/15598608.2017.1299055.
  48. Zhou, Y. D. and Xu, H.  (2017). Composite designs based on orthogonal arrays and definitive screening designs. Journal of the American Statistical Association, 112:520, 1675-1683. DOI: 10.1080/01621459.2016.1228535
  49. Xiao, Q. and Xu, H.  (2017). Construction of Maximin Distance Latin Squares and Related Latin Hypercube Designs. Biometrika, 104,  455-464.
  50. Xiao, Q. and Xu, H.  (2018).  Construction of Maximin Distance Designs via Level Permutation and ExpansionStatistica Sinica, 28, 1395-1414.
  51. Wang, Y., Yang, J. and Xu, H. (2018).  On Connection Between Maximin Distance Designs and Orthogonal Designs. Biometrika, 105, 471-477.
  52. Wang, L., Xiao, Q. and Xu, H. (2018). Optimal Maximin L1-distance Latin Hypercube Designs Based on Good Lattice Point Designs. Annals of Statistics, 46(6B), 3741-3766. [pdf]
  53. Xiao, Q., Wang, L. and Xu, H. (2019).  Application of Kriging Models for a Drug Combination Experiment on Lung Cancer. Statistics in Medicine, 38, 236-246.
  54. Sun, F., Wang, Y. and Xu, H. (2019). Uniform Projection Designs. Annals of Statistics, 47, 641-661. [pdf]
  55. Vazquez, A. R. and Xu, H. (2019). Construction of Two-Level Nonregular Designs of Strength Three With Large Run Sizes. Technometrics, 61, 341-353.
  56. Wang, A., Xu, H. and Ding, X. (2020). Simultaneous Optimization of Drug Combination Dose-Ratio-Sequence with Innovative Design and Active Learning. Advanced Therapeutics, 3(4), 1900135.
  57. Ding, X., Chang, V. H. S., Li, Y., Xu, H., Ho, C.-M., Ho, D. and Yen, Y. (2020). Harnessing an Artificial Intelligence Platform to Dynamically Individualize Combination Therapy for Treating Colorectal Carcinoma in a Rat ModelAdvanced Therapeutics, 3(4), 1900127.
  58. Tang, Y. and Xu, H.  (2021). Wordlength Enumerator for Fractional Factorial DesignsAnnals of Statistics, 49, 255-271. [pdf]
  59. Yang, J., Sun, F. and Xu, H. (2021). A Component-Position Model, Analysis and Design for Order-of-Addition Experiments Technometrics, 63, 212-224..
  60. Xiao, Q. and Xu, H.  (2021). A Mapping-based Universal Kriging Model for Order-of-addition Problems in Drug Combination Studies. Computational Statistics and Data Analysis, 157, 107155.
  61. Wang, L., Elmstedt, J., Wong, W. K., and Xu, H.  (2021). Orthogonal Subsampling for Big Data Linear Regression. Annals of Applied Statistics, 15(3), 1273-1290. 
  62. Wang, Y., Sun, F. and Xu, H. (2022). On design orthogonality, maximin distance and projection uniformity for computer experiments. Journal of the American Statistical Association, 117, 375-385.
  63. Tian, Y. and Xu, H.  (2022). A Minimum Aberration-Type Criterion for Selecting Space-Filling Designs. Biometrika,109(2), 489-501.
  64. Zhou, Q., Li, W. and Xu, H. (2023). Utilizing Individual Clear Effects for Intelligent Factor Allocations and Design Selections. Journal of Quality Technology, 55(1), 3-17.
  65. Burton, H., Xu, H. and Yi, Z. (2022). Design of Computer Experiments for Developing Seismic Surrogate Models. Earthquake Spectra, 38(1), 384-406. [pdf]
  66. Wang, L. and Xu, H. (2022). A Class of Multilevel Nonregular Designs for Studying Quantitative Factors. Statistica Sinica, 32, 825-845.
  67. Stokes, Z. and Xu, H.  (2022). A Position-Based Approach for Design and Analysis of Order-of-Addition Experiments. Statistica Sinica, 32(3), 1467-1488.
  68. Wu, H.,  Amirfakhri, S.,  Hollandsworth, H.,  Filemoni, F., Liu, Y.,  Lin, H.,  Li, J. Y. S., Xu, H.,   Chien, S.,  Bouvet, M., and Wang, Y. (2022). Monocytes Engineered with iSNAP Inhibit Human B-Lymphoma Progression. Bioengineering & Translational Medicine, 7(2), e10285.
  69. Luna, J., Jaynes, J.,  Xu, H., Wong, W. K. (2022). Orthogonal Array Composite Designs for  Drug Combination Experiments with Applications to Tuberculosis. Statistics in Medicine, 41(17), 3380--3397.
  70. Wang, L., Xu, H. and Liu, M.-Q. (2023). Fractional factorial designs for Fourier cosine models. Metrika,  86, 373--390.
  71. Shi, C., Chiu, A. K., and Xu, H. (2023). Evaluating Designs for Hyperparameter Tuning in Deep Neural Networks. The New England Journal of Statistics in Data Science, 1(3), 334-341.
  72. Yin, Y., Wang, L. and Xu, H. (2023). Construction of Maximin L1-Distance Latin Hypercube Designs. Electronic Journal of Statistics, 17, 3942-3968.
  73. Stokes, Z. and Xu, H.  (2024). Designs for Order-of-Addition Screening Experiments Statistica Sinica, 34(1), 399--419.
  74. Tian, Y. and Xu, H. (2024). Stratification Pattern Enumerator and its Applications. Journal of the Royal Statistical Society Series B: Statistical Methodology, 86(2), 364-385.
  75. Zhu, L., Man, C.-W., Harrison, R. E. S., Wu, Z., Limsakul, P., Peng, Q., Hashimoto, M., Mamaril, A. P., Xu, H.,  Liu, L., and Wang, Y. (2024). Engineering a Programmed Death-Ligand 1-Targeting Monobody Via Directed Evolution for SynNotch-Gated Cell Therapy. ACS Nano, 18 (11), 8531-8545.
  76. Vazquez, A. R. and Xu, H. (2024). An integer programming approach for constructing maximin distance designs from good lattice point sets. Statistica Sinica, 34(3),
  77. Shi, C. and Xu, H. (2023+). A Projection Space-Filling Criterion and Related Optimality Results. Journal of the American Statistical Association, in press.
  78. Stokes, Z., Wong, W. K., and Xu, H. (2023+). Metaheuristic Solutions to Order-of-Addition Design Problems. Journal of Computational and Graphical Statistics,  in press.
  79. Yuan, R., Yin, Y., Xu, H., and Liu, M.-Q. (2023+). A Construction Method for maximin L1-distance Latin hypercube designs. Statistica Sinica, 35(2).
 Last updated on May 2024.