6 papers
Reconciliation of Bayes and empirical Bayes interval estimation with application to small area estimation
Aditi Sen, Masayo Y. Hirose, Partha Lahiri
Multi-level normal hierarchical models, also interpreted as mixed effects models, play an important role in developing statistical theory in multi-parameter estimation for a wide r…
Empirical best prediction of poverty indicators via nested error regression with high dimensional parameters
Yuting Chen, Partha Lahiri, Nicola Salvati
The Nested Error Regression Model with High-Dimensional Parameters (NERHDP) is extended to address challenges in small area poverty estimation. A robust and flexible framework is p…
Impact of existence and nonexistence of pivot on the coverage of empirical best linear prediction intervals for small areas
Yuting Chen, Masayo Y. Hirose, Partha Lahiri
We advance the theory of parametric bootstrap in constructing highly efficient empirical best (EB) prediction intervals of small area means. The coverage error of such a prediction…
Improving measurement error and representativeness in nonprobability surveys
Aditi Sen, Partha Lahiri
In the age of big data, nonprobability surveys are becoming increasingly abundant. Data integration techniques involving both probability and nonprobability surveys are being exten…
Multidimensional Poverty Mapping for Small Areas
Soumojit Das, Dilshanie Deepawansa, Partha Lahiri
Many countries measure poverty based only on income or consumption. However, there is a growing awareness of measuring poverty through multiple dimensions that captures a more reas…
Effects of model misspecification on small area estimators
Yuting Chen, Partha Lahiri, Nicola Salvati
Nested error regression models are commonly used to incorporate observational unit specific auxiliary variables to improve small area estimates. When the mean structure of this mod…