Model Selection in a Composite Likelihood Framework Based on Density 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 <inline-formula> <math display="inline"> <sem...
Main Authors: | Elena Castilla, Nirian Martín, Leandro Pardo, Konstantinos Zografos |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-02-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/22/3/270 |
Similar Items
-
Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator
by: Elena Castilla, et al.
Published: (2017-12-01) -
Minimum Phi-Divergence Estimators and Phi-Divergence Test Statistics in Contingency Tables with Symmetry Structure: An Overview
by: Leandro Pardo, et al.
Published: (2010-06-01) -
Minimum Divergence Estimators, Maximum Likelihood and the Generalized Bootstrap
by: Michel Broniatowski
Published: (2021-01-01) -
Extreme Precipitation Frequency Analysis Using a Minimum Density Power Divergence Estimator
by: Yongwon Seo, et al.
Published: (2017-01-01) -
Robust Change Point Test for General Integer-Valued Time Series Models Based on Density Power Divergence
by: Byungsoo Kim, et al.
Published: (2020-04-01)