Publications

  1. Su, L. and Bondell, H. D. (2018+). Best linear estimation via minimization of relative mean squared error. Statistics and Computing (In Press).
  2. Kong, D., Bondell, H. D., and Wu, Y. (2018+). Fully efficient robust estimation, outlier detection, and variable selection via penalized regression. Statistica Sinica (In Press).
  3. Zhang, Y. and Bondell, H. D. (2018+). Variable selection via penalized credible regions with Dirichlet-Laplace global-local shrinkage priors. Bayesian Analysis (In Press).
  4. Rodriguez, S. L., Peterson, M. N., Cubbage, F. W., Sills, E. O., and Bondell, H. D. (2018). What is Private Land Stewardship? Lessons from Agricultural Opinion Leaders in North Carolina. Sustainability 10, 297.
  5. Kong, D., Bondell, H. D., and Shen, W. (2018). Outlier detection and robust estimation in nonparametric regression. Proceedings of Machine Learning Research 84, 208-216.
  6. Li, Q., Guindani, M., Reich, B. J., Bondell, H. D. and Vannucci, M. (2017). A Bayesian mixture model for clustering and selection of feature occurrence rates under mean constraints. Statistical Analysis and Data Mining 10, 393-409.
  7. Peterson, M. N., Chesonis, T., Stevenson, K. T., and Bondell, H. D. (2017). Evaluating relationships between hunting and biodiversity knowledge among children. Wildlife Society Bulletin 41, 530-536.
  8.  Mitra, R., McNeil, K. S., and Bondell, H. D. (2017). Pupillary response to complex interdependent tasks: A cognitive-load theory perspective. Behavior Research Methods 49, 1905-1919.
  9. Huque, M. H., Bondell, H. D., Carroll, R. J., and Ryan, L. (2016). Spatial regression with covariate measurement error: A semi-parametric approach. Biometrics 72, 678-686.
  10. Stevenson, K. T., Peterson, M. N., and Bondell, H. D. (2016). The influence of personal beliefs, friends, and family in building climate change concern among adolescents. Environmental Education Research, 1-14.
  11. Neely, M. L., Bondell, H. D., and Tzeng, J.-Y. (2015). A penalized likelihood approach for investigating gene-drug interactions in pharmacogenetic studies. Biometrics 71, 529-537.
  12. Li, M., Staicu, A. M., and Bondell, H. D. (2015). Incorporating covariates in skewed functional data models. Biostatistics 16, 413-426.
  13. Kong, D., Bondell, H. D., and Wu, Y. (2015). Domain selection for the varying coefficient model via local polynomial regression. Computational Statistics and Data Analysis 83, 236-250.
  14. Chitwood, M. C., Peterson, M. N., Bondell, H. D, Lashley, M. A., Brown, R. D, and Deperno, C. S. (2015). Perspectives of wildlife conservation professionals on intensive deer management. Wildlife Society Bulletin 39, 751–756.
  15. Huque, M. H., Bondell, H. D., and Ryan, L. (2014). On the impact of covariate measurement error on spatial regression modelling. Environmetrics 25, 560-570.
  16. Stevenson, K. T., Peterson, M. N., Bondell, H. D., Moore, S. E., and Carrier, S. J. (2014). Overcoming skepticism with education: Interacting influences of worldview and climate change knowledge on perceived climate change risk among adolescents. Climatic Change 126, 293-304.
  17. Jiang, L., Bondell, H. D., and Wang, H. J. (2014). Interquantile shrinkage and variable selection in regression models. Computational Statistics and Data Analysis 69, 208-219.
  18. Stevenson, K. T., Peterson, M. N., Carrier, S. J., Strnad, R. L., Bondell, H. D., Kirby-Hathaway, T., and Moore, S. E. (2014). Role of significant life experiences in building environmental knowledge and behavior among middle school students. Journal of Environmental Education 45, 163-177.
  19. Bondell, H. D. and Stefanski, L. A. (2013). Efficient robust regression via two-stage generalized empirical likelihood. Journal of the American Statistical Association 108, 644-655.
  20. Reich, B. J., Bandyopadhyay, D., and Bondell, H. D. (2013). A nonparametric spatial model for periodontal data with non-random missingness. Journal of the American Statistical Association 108, 820-831.
  21. Lin, C.-Y., Zhang, H. H., Bondell, H. D., and Zou, H. (2013). Variable selection for nonparametric quantile regression via smoothing spline analysis of variance. Stat 2, 255-268.
  22. Peterson, M.N., Bondell, H. D., Fratanduono, M. B. L., Bigsby, K., and McHale, M. (2013). Prediction indicators for voluntary carbon-offset purchases among trail runners. Journal of Sport Behavior 36, 264-275.
  23. Jiang, L., Wang, H. J., and Bondell, H. D. (2013). Interquantile shrinkage in regression models. Journal of Computational and Graphical Statistics 22, 970-986.
  24. Post, J. B. and Bondell, H. D. (2013). Factor selection and structural identification in the interaction ANOVA model. Biometrics 69, 70-79.
  25. Sharma, D. B., Bondell, H. D., and Zhang, H. H. (2013). Consistent group identification and variable selection in regression with correlated predictors. Journal of Computational and Graphical Statistics 22, 319-340.
  26. Stevenson, K. T., Peterson, M. N., Bondell, H. D., Mertig, A. G., and Moore, S. E. (2013). Environmental, institutional, and demographic predictors of environmental literacy among middle school children. PLoS ONE 8, e59519.
  27. Bondell, H.D. and Reich, B. J. (2012). Consistent high-dimensional Bayesian variable selection via penalized credible regions. Journal of the American Statistical Association 107, 1610-1624.
  28. Peterson, M. N., Thurmond, B., McHale, M., Rodriguez, S., Bondell, H. D., and Cook, M. (2012). Predicting native plant landscaping preferences in urban areas. Sustainable Cities and Society 5, 70-76.
  29. Reich, B. J., Kalendra, E., Storlie, C. B., Bondell, H. D., and Fuentes, M. (2012). Variable selection for high-dimensional Bayesian density estimation: Application to human exposure simulation. Journal of the Royal Statistical Society C 61, 47-66.
  30. Dalrymple, C. J., Peterson, M. N., Cobb, D. T., Sills, E. O., Bondell, H. D., and Dalrymple, D. J. (2012). Estimating public willingness to fund nongame conservation through state tax initiatives. Wildlife Society Bulletin 36, 483-491.
  31. Gunes, F. and Bondell, H. D. (2012). A confidence region approach to tuning for variable selection. Journal of Computational and Graphical Statistics 21, 295-314.
  32. Rodriguez, S. L., Peterson, M. N., Cubbage, F. W., Sills, E. O., and Bondell, H. D. (2012). Private landowner interest in market-based incentive programs for endangered species habitat conservation. Wildlife Society Bulletin 36, 469-476.
  33. Reich, B. J., Bondell, H. D., and Li, L. (2011). Sufficient Dimension Reduction via Bayesian Mixture Modeling. Biometrics 67, 886-895.
  34. Storlie, C. B., Bondell, H. D., Reich, B. J. and Zhang, H. H. (2011). Surface estimation, variable selection, and the nonparametric oracle property. Statistica Sinica 21, 679-705.
  35. Reich, B. J., and Bondell, H. D. (2011). A spatial Dirichlet process mixture model for clustering population genetics data. Biometrics 67, 381-390.
  36. Bondell, H. D., Krishna, A., and Ghosh, S. K. (2010). Joint variable selection of fixed and random effects in linear mixed-effects models. Biometrics 66, 1069-1077.
  37. Freire, M., Robertson, I., Bondell, H. D., Brown, J., Hash, J., Pease, A. P., Lascelles, B. D. X. (2011). Radiographic evaluation of feline appendicular degenerative joint disease vs. macroscopic appearance of articular cartilage. Veterinary Radiology and Ultrasound 52, 239-247.
  38. Bondell, H. D., Reich, B. J., and Wang, H. (2010). Non-crossing quantile regression curve estimation. Biometrika 97, 825-838.
  39. Storlie, C. B., Bondell, H. D., and Reich, B. J. (2010). A locally adaptive penalty for estimation of functions with varying roughness. Journal of Computational and Graphical Statistics 19, 569-589.
  40. Koehler, M. L., Bondell, H. D., and Tzeng, J.-Y. (2010). Evaluating Haplotype Effects in Case-Control Studies via Penalized-Likelihood Approaches: Prospective or Retrospective Analysis? Genetic Epidemiology 34, 892-911.
  41. Reich, B. J., Bondell, H. D., and Wang, H. (2010). Flexible Bayesian quantile regression for independent and clustered data. Biostatistics 11, 337-352.
  42. Zamprogno, H., Hansen, B. D., Bondell H. D., Thomson-Sumrell, A., Simpson, W., Robertson, I., Brown, J., Pease, A., Roe, S. C., Hardie, E., Wheeler, S. J., Lascelles, B. D. X. (2010). Item generation and design testing of a questionnaire to assess degenerative joint disease-associated pain in cats. American Journal of Veterinary Research 71, 1417-1424.
  43. Tzeng, J.-Y. and Bondell, H. D. (2010). A comprehensive approach to haplotype-specific analysis by penalized likelihood. European Journal of Human Genetics 18, 95-103.
  44. Dalrymple, C. J., Peterson, M. N., Bondell, H. D., Rodriguez, S. L., Fortney, J., Cobb, D. T., and Sills, E. O. (2010). Understanding angler and hunter annual spending in North Carolina. Proceedings of the Annual Conference of the Southeastern Association of Fish and Wildlife Agencies 64, 88-94.
  45. Bondell, H. D. and Li, L. (2009). Shrinkage inverse regression estimation for model-free variable selection. Journal of the Royal Statistical Society B 71, 287-299.
  46. Bondell, H. D. and Reich, B.J. (2009). Simultaneous factor selection and collapsing levels in ANOVA. Biometrics 65, 169-177.
  47. Krishna, A., Bondell, H. D., and Ghosh, S. K. (2009). Bayesian variable selection using an adaptive powered correlation prior. Journal of Statistical Planning and Inference 139, 2665-2674.
  48. Reich, B. J., Storlie, C. B., and Bondell, H. D. (2009). Variable selection in Bayesian smoothing spline ANOVA models: Application to deterministic computer codes. Technometrics 51, 110-120.
  49. Bondell, H. D. (2008). A characteristic function approach to the biased sampling model, with application to robust logistic regression. Journal of Statistical Planning and Inference 138, 742-755.
  50. Bondell, H. D. and Reich, B. J. (2008). Simultaneous regression shrinkage, variable selection and clustering of predictors with OSCAR. Biometrics 64, 115-123.
  51. Bondell, H. D. (2008). On robust and efficient estimation of the center of symmetry. Communications in Statistics – Theory and Methods 37, 318-327.
  52. Bondell, H. D. (2007). Testing goodness-of-fit in logistic case-control studies. Biometrika 94, 487-495.
  53. Bondell, H. D., Liu, A., and Schisterman, E. F. (2007). Statistical inference based on pooled data: A moment-based estimating equation approach. Journal of Applied Statistics 34, 129-140.
  54. Schisterman, E. F., Perkins, N. J., Liu, A., and Bondell, H. D. (2005). Optimal cut-point and its corresponding Youden index to discriminate individuals using pooled blood samples. Epidemiology 16, 73-81.
  55. Bondell, H. D. (2005). Minimum distance estimation for the logistic regression model. Biometrika 92, 724-731.