2026-08-16T05:28:03Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/75452023-08-25T19:20:39Zcom_20.500.14352_14col_20.500.14352_15

Castilla González, Elena María Martín Apaolaza, Nirian Pardo Llorente, Leandro Zografos, Konstantinos 2023-06-17T08:55:55Z 2023-06-17T08:55:55Z 2020 1099-4300 10.3390/e22030270 https://hdl.handle.net/20.500.14352/7545 https://doi.org/10.3390/e22030270 https://www.mdpi.com/1099-4300/22/3/270 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. eng https://creativecommons.org/licenses/by/3.0/es/ open access Atribución 3.0 España Model Selection in a Composite Likelihood Framework Based on Density Power Divergence journal article