Name
Abstract | ||
|---|---|---|
In the problem of selecting the explanatory variables in the linear mixed model, we address the derivation of the (unconditional or marginal) Akaike information criterion (AIC) and the conditional AIC (cAIC). The covariance matrices of the random effects and the error terms include unknown parameters like variance components, and the selection procedures proposed in the literature are limited to the cases where the parameters are known or partly unknown. In this paper, AIC and cAIC are extended to the situation where the parameters are completely unknown and they are estimated by the general consistent estimators including the maximum likelihood (ML), the restricted maximum likelihood (REML) and other unbiased estimators. We derive, related to AIC and cAIC, the marginal and the conditional prediction error criteria which select superior models in light of minimizing the prediction errors relative to quadratic loss functions. Finally, numerical performances of the proposed selection procedures are investigated through simulation studies. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.jmva.2010.11.007 | J. Multivariate Analysis |
Keywords | Field | DocType |
small area estimation,linear mixed model,conditional aic,unknown parameter,restricted maximum likelihood estimator,unconditional method,secondary,akaike information criterion,62h12,restricted maximum likelihood,62b10,62e20,prediction error,error term,selection procedure,best linear unbiased predictor,proposed selection procedure,62j05,maximum likelihood,primary,fay–herriot model,conditional prediction error criterion,nested error regression model,maximum likelihood estimator,unbiased estimator,maximum likelihood estimate,loss function,consistent estimator,regression model,random effects | Econometrics,Conditional probability distribution,Akaike information criterion,Mixed model,Covariance matrix,Statistics,Restricted maximum likelihood,Generalized linear mixed model,Marginal distribution,Mathematics,Estimator | Journal |
Volume | Issue | ISSN |
102 | 3 | Journal of Multivariate Analysis |
Citations | PageRank | References |
6 | 1.33 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tatsuya Kubokawa | 1 | 36 | 11.73 |