Showing 51 - 60 of 1,351
In this paper, we suggest the new variable selection procedure, called MEC, for linear discriminant rule in the high-dimensional setup. MEC is derived as a second-order unbiased estimator of the misclassication error probability of the lin- ear discriminant rule. It is shown that MEC not only...
Persistent link: https://www.econbiz.de/10011010132
   The paper develops empirical Bayes and benchmarked empirical Bayes estimators of positive small area means under multiplicative models. A simple example will be estimation of per capita income for small areas. It is now well-understood that small area estimation needs explicit,...
Persistent link: https://www.econbiz.de/10010741291
The paper addresses the problem of selecting variables in the two-stage sampling models characterized as a linear mixed model. We obtain the Empirical Bayes Information Criterion (EBIC) using a prior distribution on regression coefficients with an unknown hyper-parameter. It is shown that EBIC...
Persistent link: https://www.econbiz.de/10004981178
In this paper, we consider the problem of selecting the variables of the fixed effects in the linear mixed models where the random effects are present and the observation vectors have been obtained from many clusters. As the variable selection procedure, we here use the Akaike Information...
Persistent link: https://www.econbiz.de/10004998478
The empirical best linear unbiased predictor (EBLUP) or the empirical Bayes estimator (EB) in the linear mixed model is recognized useful for the small area estimation, because it can increase the estimation precision by using the information from the related areas. Two of the measures of...
Persistent link: https://www.econbiz.de/10005041989
In the small area estimation, the empirical best linear unbiased predictor (EBLUP) or the empirical Bayes estimator (EB) in the linear mixed model is recognized useful because it gives a stable and reliable estimate for a mean of a small area. In practical situations where EBLUP is applied to...
Persistent link: https://www.econbiz.de/10004964264
The Akaike Information Criterion (AIC) is developed for selecting the variables of a nested error regression model where an unobservable random effect is present. Using the idea of decomposing the marginal distribution into two parts of 'within' and 'between' analysis of variance, we derive the...
Persistent link: https://www.econbiz.de/10004999294
In the small area estimation, the empirical best linear unbiased predictor (EBLUP) in the linear mixed model is recognized useful because it gives a stable and reliable estimate for a mean of a small area. In practical situations where EBLUP is applied to real data, it is important to evaluate...
Persistent link: https://www.econbiz.de/10004999304
Estimation of small area means under a basic area level model is studied, using an empirical Bayes (best) estimator or a weighted estimator with fixed weights. Mean squared errors (MSEs) of the estimators and nearly unbiased (or exactly unbiased) estimators of MSE are derived under three...
Persistent link: https://www.econbiz.de/10005025236
In this paper, we consider the problem of selecting variables from the fixed effects as well as from the random effects when observations from several clusters are available to provide consistent estimators of some unknown parameters. We obtain Bayesian Information Criterion (BIC) using the...
Persistent link: https://www.econbiz.de/10005628855