Research Codes
Visit my Github page for computer codes and brief descriptions of several projects.
Published and Accepted Articles
20. Gutierrez, R. and Guhaniyogi, R. (2021). Bayesian Dynamic Feature Partitioning in High-Dimensional Regression with Big Data. [full text] , Accepted
19. Spencer, D., Guhaniyogi, R. and Prado, R. (2020). Bayesian Mixed Effect Sparse Tensor Response Regression Model with Joint Estimation of Activation and Connectivity. Psychometrika, Accepted, [full text]
18. Guhaniyogi, R. (2020). High Dimensional Bayesian Regularization in Regressions Involving Symmetric Tensors.Accepted, Proceedings of 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. [full text]
17. Guha, S. and Guhaniyogi, R. (2020). Bayesian Generalized Sparse Symmetric Tensor-on-Vector Regression.Technometrics, Accepted, [full text]
16. Guhaniyogi, R. (2020). Bayesian Methods for Tensor Regressions.Wiley StatsRef: Statistical References Online, Accepted, [full text]
15. Guhaniyogi, R. and Rodriguez, A. (2020). Joint Modeling of Longitudinal Relational Data and Exogenous Variables.Bayesian Analysis, 15 (2), 477-503. [full text]
14. Guhaniyogi, R. and Sanso, B. (2019). Large Multiscale Spatial Modeling using Tree Shrinkage Priors. Statistica Sinica, 30, 2023-2050. [full text]
13. Heaton, M.J., Datta, A., Finley, A., Furrer, R., Guhaniyogi, R., Gerber, F., Gramacy, R. B., Hammerling, D., Katzfuss, M., Lindgren, F., Nychka, D. W., Sun, F. and Mangion, A. Z. (in alphabetical order) (2019). Methods for Analyzing Large Spatial Data: A Review and Comparison. 24, 398-425. Journal of Agricultural, Biological and Environmental Statistics [full text]
12. Guhaniyogi, R. and Banerjee, S. (2019). Multivariate Spatial Meta Kriging. Statistics and Probability Letters, [full text]
11. Guhaniyogi, R. and Banerjee, S. (2018). Meta-Kriging: Scalable Bayesian Modeling and Inference for Massive Spatial Datasets. Technometrics, 60(4), 430-444 [full text] [code and details]
10. Guhaniyogi, R., Qamar, S. and Dunson, D.B. (2018). Bayesian Conditional Density Filtering. Journal of Computational and Graphical Statistics, 27(3), 653-672 [full text] [code and details]
9. Guhaniyogi, R., Qamar, S. and Dunson, D.B. (2017). Bayesian Tensor Regression. Journal of Machine Learning Research, 18, 1-31. [full text] [code and details]
8. Guhaniyogi, R.(2017). Bayesian Nonparametric Areal Wombling for Small Scale Maps with an Application to Urinary Bladder Cancer Data from Connecticut. Statistics in Medicine, DOI:10.1002/sim.7408 [full text] [code and details]
7. Guhaniyogi, R. (2017). Convergence Rate of Bayesian Supervised Tensor Modeling with Multiway Shrinkage Priors. Journal of Multivariate Analysis, 160, 157-168 [full text]
6. Guhaniyogi, R. (2017). Multivariate Bias Adjusted Tapered Predictive Process Models. Spatial Statistics, 21, 42-65 [full text] [code and details]
5. Guhaniyogi, R. and Dunson, D.B. (2016). Compressed Gaussian Process for Manifold Regression. Journal of Machine Learning Research, 17, 1-26. [full text]
4. Guhaniyogi, R. and Dunson, D.B. (2016). Bayesian Compressed Regression. Journal of the American Statistical Association, Theory & Methods, 110, 1500-1514. [full text]
3. Belani, H.K., Sekar, P., Guhaniyogi, R., Abraham, A., Bohjanen, P.R. and Bohjanen, K. (2014). Human papillomavirus vaccine acceptance among young men in Bangalore, India. International Journal of Dermatology, 53, 486-491. [full text]
2. Guhaniyogi, R., Finely, A.O., Banerjee, S. and Kobe, R. (2013). Modeling Low-rank Spatially-Varying Cross-Covariances using Predictive Process with Application to Soil Nutrient Data. Journal of Agricultural, Biological and Environmental Statistics, 18, 274-298. [full text]
1. Guhaniyogi, R., Finely, A.O., Banerjee, S. and Gelfand, A.E. (2011). Adaptive Gaussian predictive process models for large spatial datasets. Environmetrics, 22, 997-1007. [full text]
Invited Discussions
Guhaniyogi, R. and Banerjee, S. (2012). Comment on "Article by Lum and Gelfand." Bayesian Analysis, 7, 59-62 [full text]
Guhaniyogi, R. and Banerjee, S. (2012). Discussion on "Inference for Size Demography from Point Pattern Data using Integral Projection Models." Journal of Agricultural, Biological and Environmental Statistics, 17, 678-681 [full text]
Articles under Review or in Revision
6. Guhaniyogi, R., Li, C., Savitsky, T. and Srivastava, S. (2021+). Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior. [full text] , Under Review
5. Guhaniyogi, R. (2021+). Privacy Preserving Efficient Computation in Bayesian High Dimensional Regression With Big Data Using Gaussian Scale Mixture Priors. [full text] , Under Review
4. Guhaniyogi, R., Spencer, D. (2021+). Bayesian Tensor Response Regression With an Application to Brain Activation Studies. [full text] , Accepted Subject to Minor Revision
3. Guhaniyogi, R., Li, C., Savitsky, T. and Srivastava, S. (2021+). A Divide-and-Conquer Bayesian Approach to Large-Scale Kriging. [full text] , Revision Requested
2. Guha, S. and Guhaniyogi, R. (2021+). Bayesian Supervised Clustering of Undirected Networks with Applications to Brain Connectome Data. [full text] , Under Review
1. Guhaniyogi, R. and Guha, S. (2021+). Convergence Rate for Predictive Densities of Bayesian Generalized Scalar on Symmetric Tensor Regressions. [full text] , Under Review
Book Chapters
Bhandari, S., Dutta, R. and Guhaniyogi, R. (2009). Study of Optimal Adaptive Rule in Testing Problems. Advances in Multivariate Statistical Methods (Chapter 16). Singapore: World Scientific. [full text]