Partha Lahiri

Professor, Statistics Program
Department of Mathematics

Professor and Director
Joint Program in Survey Methodology (JPSM)

University of Maryland
College Park, MD 20742


CV
EVS, Stat


Contact Information



Basic Information on the RIT topic
SiT Special Issue 2020
IMS Monograph on Model Selection (ed. P.Lahiri)
RIT SAE Sessions

Next RIT Presentation
May 11, 3:30-4:30 UN Toolkit on small area estimation for the Sustainable Development Goals
Speakers:
Haoyi Chen, Coordinator, Inter-Secretariat Working Group on Household Surveys, United Nations
Yongyi Min, Chief, Sustainable Development Goal Monitoring Section, UN Statistics Division, United Nations
Abstract
Slides

Panelists:
William Bell (U.S. Census Bureau), Carolina Casas-Cordero (Universidad Católica de Chile), Carolina Franco (U.S. Census Bureau), Graham Kalton (JPSM), Benmei Liu (U.S. National Cancer Institute), Monica Pratesi (University of Pisa, Italy), J.N.K. Rao (Carleton University, Canada)

Previous RIT Presentations
Feb 2 and Feb 9: An introduction to small srea estimation (Speaker: Partha Lahiri, University of Maryland College Park)
Slides

Feb 16: Parametric bootstrap methods in small area estimation (Speaker: Snigdhansu Chatterjee, University of Minnesota)
Slides

Feb 23: Data fusion for solving small area estimation (Speaker: Ben Kedem, University of Maryland College Park)
Slides
Paper

March 2: SAE Projects in the World Bank (Speaker: David Newhouse, World Bank Group)
Slides
Paper

March 9: SAE in Transportation (Speaker: Cinzia Cirillo, University of Maryland College Park)
Slides
Abstract

March 23: SAE method for employee compensation (Speaker: Andreea Erciulescu, Westat)
Slides
Paper

March 30: Small area estimation in the presence of measurement error in the covariates (Speaker: Carolina Franco, Census Bureau)
Slides
Paper

April 6: Parametric bootstrap for SAE (Speaker: Takumi Saegusa, University of Maryland College Park)
Paper
Slides

April 13:
3:30-4 PM: Parametric Bootstrap for SAE (Speaker: Sheyda Peyman, AMSC-UMD student)
Paper to discuss
Slides

4-4:30 PM: Adjusted Maximum Likelihood methods for SAE (Speaker: Phillip Koshute, AMSC-UMD student)
Paper to discuss
Slides

April 20: Hybrid BRR and Parametric-Model Variance Estimates for Small Domains in Large Surveys (Speaker: Eric Slud, University of Maryland College Park)
Slides
Slides
Paper

April 27: Post-election Analysis of Presidential Election/Poll Data: Liars Continued to Lie But What Have Changed? (Speaker: Jiming Jiang, University of California, Davis)
Abstract
Slides

May 4: Implementation of model-based estimates in support of the USDA NASS crops county estimates program (Speaker: Nathan Cruze and Lu Chen, NASS/USDA)
Cruze et al. (2019)
Erciulescu et a. (2018)

Research Papers

COVID-19 Related Papers
Sen, A. and Lahiri, P. (2020), Estimation of mask effectiveness perception for small domains using multiple data sources, unpublished manuscript.

Bayesian
Hirose, M. and Lahiri, P. (2020), Multi-Goal Prior Selection: A Way to Reconcile Bayesian and Classical Approaches for Random Effects Models , Journal of the American Statistical Association.
Ganesh, N. and Lahiri, P. (2008), A new class of average moment matching priors , Biometrika.

Probabilistic Record Linkage
Han, M. and Lahiri, P. (2018), Statistical Analysis with Linked Data , International Statistical Review.
Lahiri, P. and Larsen, M. (2005), Regression analysis with linked data , Journal of the American Statistical Association.

Empirical Best Prediction Methods
Hirose, M. and Lahiri, P. (2018),Estimating variance of random effects to solve multiple problems simultaneously , Annals of Statistics.
Yoshimori, M. and Lahiri, P. (2014),A second-order efficient empirical Bayes confidence interval , Annals of Statistics.
Yoshimori, M. and Lahiri, P. (2014),A new adjusted maximum likelihood method for the Fay-Herriot small area model , Journal of Multivariate Analysis.
Jiang, J. and Lahiri, P. (2006),Mixed model prediction and small area estimation, Editor's invited discussion paper , Test.
Datta, G. and Lahiri, P. (2000),A unified measure of uncertainty of estimated best linear unbiased predictors in small area estimation problems , Statistica Sinica.

Resampling Methods
Jiang, J, Lahiri, P. and Nguyen, T. (2018),A Unified Monte-Carlo Jackknife for Small Area Estimation after Model Selection , Annals of Mathematical Sciences and Applications.
Chatterjee, S., Lahiri, P. and Li, H. (2008), On small area prediction interval problems , Annals of Statistics.
Jiang, J, Lahiri, P. and Wan, S. (2003),Jackknifing the mean squared error of empirical best predictor , Annals of Statistics.
Butar, F. and Lahiri, P. (2003),On the measures of uncertainty of empirical Bayes small-area estimators , Journal of Statistical Planning and Inference.


           Links

The UMCP Statistics Program home page.

The UMCP Math Department home page.

The Joint Program in Survey Methodology (JPSM).

The University of Maryland home page.


© Partha Lahiri, December 14, 2020.