Software
Here is some code related to previous published work. The large majority of Professor Bondell’s recent publications have affiliated code that is either included in the supplementary materials of the publishing journal or linked to a repository listed in the paper, rather than archived here.
- 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.
- 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.
- Jiang, L., Wang, H. J., and Bondell, H. D. (2013). Interquantile shrinkage in regression models. Journal of Computational and Graphical Statistics 22, 970-986.
- 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.
- 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.
- 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.
- Reich, B. J., Bondell, H. D., and Li, L. (2011). Sufficient Dimension Reduction via Bayesian Mixture Modeling. Biometrics 67, 886-895.
- Reich, B. J., and Bondell, H. D. (2011). A spatial Dirichlet process mixture model for clustering population genetics data. Biometrics 67, 381-390.
- Bondell, H. D., Reich, B. J., and Wang, H. (2010). Non-crossing quantile regression curve estimation. Biometrika 97, 825-838.
- 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.
- Reich, B. J., Bondell, H. D., and Wang, H. (2010). Flexible Bayesian quantile regression for independent and clustered data. Biostatistics 11, 337-352.
R code for Independent Data
R Code for Clustered Data (1) Conditional Model (2) Marginal Model
- 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.
- Bondell, H. D. and Reich, B. J. (2009). Simultaneous factor selection and collapsing levels in ANOVA. Biometrics 65, 169-177.
- 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.
- 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.
- Bondell, H. D. and Reich, B. J. (2008). Simultaneous regression shrinkage, variable selection and clustering of predictors with OSCAR. Biometrics 64, 115-123.
- Bondell, H. D. (2007). Testing goodness-of-fit in logistic case-control studies. Biometrika 94, 487-495.