Castilla Elena, Martín Nirian, Pardo Leandro, Zografos Konstantinos
Interdisciplinary Mathematics Institute and Department of Statistics and O.R. I, Complutense University of Madrid, 28040 Madrid, Spain.
Interdisciplinary Mathematics Institute and Department of Financial and Actuarial Economics & Statistics, Complutense University of Madrid, 28003 Madrid, Spain.
Entropy (Basel). 2020 Feb 27;22(3):270. doi: 10.3390/e22030270.
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.
本文提出了一种基于密度幂散度测度的复合似然框架下的模型选择准则，以及复合最小密度幂散度估计量，该估计量依赖于一个调整参数α。引入这样一个准则后，建立了一些渐近性质。我们进行了一项模拟研究和两个数值例子，以指出所引入的模型选择准则的稳健性。
