4 papers
Small area learning
Katarzyna Reluga, Nicola Salvati, Setareh Ranjbar +2
Small area estimation (SAE) traditionally borrows strength across domains through a prespecified working model. We introduce small area learning (SAL), a learner-agnostic framework…
A Partial Fay-Herriot model for Small Area Estimation: Estimating district-level consumption in Mozambique
Francesco Schirripa Spagnolo, Nicola Salvati, Enrico Fabrizi
This paper proposes a new small area estimation approach that integrates Partial Least Squares within the Fay-Herriot model to address the challenges posed by high-dimensional and…
Temporal M-quantile models and robust bias-corrected small area predictors
María Bugallo Porto, Domingo Morales González, Nicola Salvati +1
In small area estimation, it is a smart strategy to rely on data measured over time. However, linear mixed models struggle to properly capture time dependencies when the number of…
Accounting for Mismatch Error in Small Area Estimation with Linked Data
Enrico Fabrizi, Nicola Salvati, Martin Slawski
In small area estimation different data sources are integrated in order to produce reliable estimates of target parameters (e.g., a mean or a proportion) for a collection of small…