Small area estimation using reduced rank regression models

von Rosen, Tatjana; von Rosen, Dietrich

doi:10.1080/03610926.2019.1586946

Abstract

Small area estimation techniques have got a lot of attention during the last decades due to their important applications in survey studies. Mixed linear models and reduced rank regression analysis are jointly used when considering small area estimation. Estimates of parameters are presented as well as prediction of random effects and unobserved area measurements.

Keywords

Growth curve model; mixed linear model; reduced rank regression

Published in

Communications in Statistics - Theory and Methods
2020, volume: 49, number: 13, pages: 3286-3297
Publisher: TAYLOR & FRANCIS INC

SLU Authors

von Rosen, Dietrich
- Department of Energy and Technology, Swedish University of Agricultural Sciences
- Linköping University

UKÄ Subject classification

Probability Theory and Statistics

Publication identifier

DOI: https://doi.org/10.1080/03610926.2019.1586946

Permanent link to this page (URI)

https://res.slu.se/id/publ/100606