Model selection using union-intersection principle for non nested models

DOI10.1080/03610926.2015.1024863zbMath1360.62076OpenAlexW2551959944MaRDI QIDQ2979945

Hamid Lorestani, Abdolreza Sayyareh

Publication date: 27 April 2017

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2015.1024863

zbMATH Keywords

model selectionunion-intersection principlefolded normalcompeting modelsnon nested models

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Parametric hypothesis testing (62F03)

Cites Work

• Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
• On the selection of forecasting models
• Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models
• Simulation based selection of competing structural econometric models
• A non-Gaussian multivariate distribution with all lower-dimensional Gaussians and related families
• Estimating a difference of Kullback-Leibler risks using a normalized difference of AIC
• Information criteria for selecting possibly misspecified parametric models
• On the exact distribution of the maximum of absolutely continuous dependent random variables
• Empiricial Comparison between Some Model Selection Criteria
• Economic tolerance design for folded normal data
• Nonlinear Regression with Dependent Observations
• Model selection tests for nonlinear dynamic models
• A new look at the statistical model identification

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