Research Interests:  Survey Sampling, Small Area Estimation,  Bayes and Empirical 

                                     Bayes Methods, Social and Environmental Statistics, Biostatistics,    

                                    Statistical Methods for Gene Expression Data

 

 

Recent Grants:    National Science Foundation, 2006-2008. Principal Investigator

                                   National Science Foundation, 2003-2006. Principal Investigator

                                  USDA Natural Resources Conservation Service, continuous, Co-Principal Investigator

                                  National Institute of Health, 2001-2004, Co-Principal Investigator

 

 

Selected Publications:

 

                  Lahiri, S.N., Maiti, T., Katzoff, M., and Parsons, V. (2006) Resampling based empirical prediction:

                                      An application to small area estimation. To appear in Biometrika.

 

                  Hall, P.,and  Maiti, T. (2006). Nonparametric estimation of mean squared prediction error in nested-error regression

                                      models. Annals of Statistics, 34, 1733-1750.

 

                  Banerjee, T., Maiti, T., and Mukhopadhyay, P. (2006). Classification of pathological stage of prostate cancer patients

                                       using penalized splines. Computational Statistics and Data Analysis, 51, 1147-1155.

 

                 Maiti, T., and Mukhopadhyay, P. (2006). Comparison of statistical classification methods based on a prostate cancer

                                        study.  To appear in Calcutta Statistical Association Bulletin.

 

                 Hall, P.,and  Maiti, T. (2006). On bootstrap methods for small area prediction. Journal of Royal Statistical Society, Series  

                                      B, 68, 221-238.

 

                 Slud, E.V. and Maiti, T. (2006). MSE estimation in transformed Fay-Herriot models.  Journal of Royal Statistical Society,

                                          Series B, 68, 239-257.

 

                 Chakraborty, S., Ghosh, M., Maiti, T., and Tewari, A. (2005). Bayesian neural networks for bivariate binary data: An  

                                            application to prostate cancer study.  To appear in Statistics in Medicine.  

 

                 Roy, S., Banerjee, T., and Maiti, T. (2004). Measurement error model for binary responses when responses are subject to   

                               classification errors.  Statistics in Medicine, 24, 269-283.

 

                 Ghosh, M.,  Maiti, T., Kim, D., Chakraborty, S. and Tewari, A. (2004). Bayesian neural network modeling in prostate

                                     cancer detection. Journal of the American Statistical Association, 99, 601-608.

 

               Ghosh, M. and Maiti, T. (2004). Small area estimation based on natural exponetial family-quadratic variance function  

                                        models and survey weights. Biometrika, 91, 95-112.

 

               Sinha, D., and Maiti, T. (2004). A Bayesian approach for the analysis of panel-count data with dependent termination,

                                     Biometrics,  60, 34-40.

 

               Maiti, T. (2004). Applying jackknife method of mean squared prediction error estimation in SAIP,  Statistics in Transition,

                               6, 685-695 (Special Issue on small area estimation).

 

               Maiti, T. (2003). Modeling small area effects using mixture of Gaussians. Sankhya (Indian Journal of Statistics), 65, 612-

                                           625.