The model selection criterion AICu.

DOI10.1016/S0167-7152(96)00192-7zbMath1064.62541MaRDI QIDQ1380660

Allan McQuarrie, Robert H. Shumway, Chih-Ling Tsai

Publication date: 1997

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05)

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Clustering bivariate mixed-type data via the cluster-weighted model ⋮ Biclustering models for two-mode ordinal data ⋮ Improved model selection criteria for SETAR time series models ⋮ Mixture-based clustering for the ordered stereotype model ⋮ Erratum to: The Generalized Linear Mixed Cluster-Weighted Model ⋮ Predictive density criterion for SETAR models ⋮ Unnamed Item ⋮ On the Least Squares Estimation of Multiple-Threshold-Variable Autoregressive Models ⋮ Bootstrap-based model selection criteria for beta regressions ⋮ Model selection criteria in beta regression with varying dispersion ⋮ Information criteria for nonlinear time series models ⋮ Nonlinear stochastic inflation modelling using SEASETARs. ⋮ A jackknife type approach to statistical model selection ⋮ A deviance-based criterion for model selection in GLM ⋮ Simultaneous variable selection for heteroscedastic regression models ⋮ Model selection in orthogonal regression ⋮ Hypothesis Testing for Mixture Model Selection ⋮ Handling non-ignorable dropouts in longitudinal data: a conditional model based on a latent Markov heterogeneity structure ⋮ The generalized linear mixed cluster-weighted model

Cites Work

• Asymptotically efficient selection of the order of the model for estimating parameters of a linear process
• A Bayesian analysis of the minimum AIC procedure
• Statistical predictor identification
• Regression and time series model selection in small samples
• An optimal selection of regression variables
• Some Comments on C P
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

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