Composite likelihood methods: Rao-type tests based on composite minimum density power divergence estimator

2019 ◽  
Author(s):  
E. Castilla ◽  
N. Martín ◽  
L. Pardo ◽  
K. Zografos
Keyword(s):  
Composite Likelihood ◽  
Likelihood Methods ◽  
Density Power Divergence ◽  
Minimum Density ◽  
Power Divergence

scholarly journals Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator

Entropy ◽  
2017 ◽  
Vol 20 (1) ◽  
pp. 18 ◽  
Author(s):  
Elena Castilla ◽  
Nirian Martín ◽  
Leandro Pardo ◽  
Konstantinos Zografos
Keyword(s):  
Composite Likelihood ◽  
Likelihood Methods ◽  
Density Power Divergence ◽  
Minimum Density ◽  
Power Divergence

scholarly journals Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator

2017 ◽  
Author(s):  
Elena Castilla ◽  
Nirian Martín ◽  
Leandro Pardo ◽  
Konstantinos Zografos
Keyword(s):  
Asymptotic Properties ◽  
Wald Test ◽  
Composite Likelihood ◽  
Test Statistics ◽  
Test Statistic ◽  
Density Power Divergence ◽  
Minimum Density ◽  
New Family ◽  
Robust Version ◽  
Power Divergence

In this paper a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator. This new family of test statistics will be called Wald-type test statistics. The problem of testing a simple and a composite null hypothesis is considered and the robustness is studied on the basis of a simulation study. Previously, the composite minimum density power divergence estimator is introduced and its asymptotic properties are studied.

Minimum density power divergence estimator for GARCH models

Test ◽  
2008 ◽  
Vol 18 (2) ◽  
pp. 316-341 ◽  
Author(s):  
Sangyeol Lee ◽  
Junmo Song
Keyword(s):  
Garch Models ◽  
Density Power Divergence ◽  
Minimum Density ◽  
Power Divergence

scholarly journals Model Selection in a Composite Likelihood Framework Based on Density Power Divergence

Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 270
Author(s):  
Elena Castilla ◽  
Nirian Martín ◽  
Leandro Pardo ◽  
Konstantinos Zografos
Keyword(s):  
Model Selection ◽  
Simulation Study ◽  
Asymptotic Properties ◽  
Selection Criterion ◽  
Composite Likelihood ◽  
Tuning Parameter ◽  
Density Power Divergence ◽  
Numerical Examples ◽  
Model Selection Criterion ◽  
Power Divergence

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.

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