RT Journal Article
T1 Information criteria for Fay–Herriot model selection
A1 Marhuenda García, Yolanda
A1 Morales, Domingo
A1 Pardo Llorente, María del Carmen
AB The selection of an appropriate model is a fundamental step of the data analysis in small area estimation. Bias corrections to the Akaike information criterion, AIC, and to the Kullback symmetric divergence criterion, KIC, are derived for the Fay–Herriot model. Furthermore, three bootstrap-corrected variants of AIC and of KIC are proposed. The performance of the eight considered criteria is investigated with a simulation study and an application to real data. The obtained results suggest that there are better alternatives than the classical AIC.
PB Elsevier Science
SN 0167-9473
YR 2014
FD 2014
LK https://hdl.handle.net/20.500.14352/35161
UL https://hdl.handle.net/20.500.14352/35161
LA eng
NO Ministerio de Economía y Competitividad (MINECO)
DS Docta Complutense
RD 7 abr 2025