Small Area Estimation
Description:
This track invites presentations on topics of research emerging from statistical applications which involve the use of Small Area Estimation (SAE) methods. The track addresses, in a good balance: (i) theoretical and methodological developments in small area estimation and related fields, (ii) computation-intensive techniques including simulation studies, and (ii) practical applications of small area estimation methods, including their potential uses in various research areas and official statistics. The track is intended to be a meeting point to create a specialized subgroup Small Area Estimation within the ERCIM Working Group on Computing & Statistics. The track is especially concerned in contributions containing original theoretical contributions of direct or potential value in applications.
Focus:
- Robust and nonparametric methods in SAE
- Bayesian methods in SAE
- Spatial methods in SAE
- Econometric and time-dependent methods in SAE
- Mean squared error estimation
- Poverty mapping
- SAE in official statistics
Full papers containing a strong computational or data analytic component will be considered for publication in the Special Topic on Small Area Estimation of the journal Computational Statistics and Data Analysis . The papers should be submitted as ordinary papers, but the authors should specify in the cover letter that they have been presented at ERCIM09 (Small Area Estimation). All submissions must contain original unpublished work not being considered for publication elsewhere. Submissions will be refereed according to standard procedures for CSDA.
Co-Chairs:
- Domingo Morales, Universidad Miguel Hernandez de Elche, Spain
- Isabel Molina, University Carlos III de Madrid, Spain
Created by Computing & Statistics 2007