RT Journal Article
T1 Model Selection in a Composite Likelihood Framework Based on Density Power Divergence
A1 Castilla González, Elena María
A1 Martín Apaolaza, Nirian
A1 Pardo Llorente, Leandro
A1 Zografos, Konstantinos
AB This paper presents a model selection criterion in a composite likelihood framework based on density power divergence measures and in the composite minimum density power divergence estimators, which depends on an tuning parameter α. After introducing such a criterion, some asymptotic properties are established. We present a simulation study and two numerical examples in order to point out the robustness properties of the introduced model selection criterion.
PB https://www.mdpi.com/
SN 1099-4300
YR 2020
FD 2020
LK https://hdl.handle.net/20.500.14352/7545
UL https://hdl.handle.net/20.500.14352/7545
LA eng
DS Docta Complutense
RD 10 abr 2025