PENERAPAN EMPIRICAL BEST LINEAR UNBIASED PREDICTION FAY HERRIOT (EBLUP FH) DAN SPATIAL EBLUP FH PADA DATA TRANSFORMASI LOGARITMA
نویسندگان
چکیده
منابع مشابه
Parametric transformed Fay-Herriot model for small area estimation
Consider the small area estimation when positive area-level data like income, revenue, harvests or production are available. Although a conventional method is the logtransformed Fay-Herriot model, the log-transformation is not necessarily appropriate. Another popular method is the Box-Cox transformation, but it has drawbacks that the maximum likelihood estimator (ML) of the transformation param...
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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 uncertainty of EBLUP is the estimation of the mean squared error (MSE) and the confidence interval, which h...
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• In this paper it is proposed a spatio-temporal area level linear mixed model involving spatially correlated and temporally autocorrelated random effects. An empirical best linear unbiased predictor (EBLUP) for small area parameters has been obtained under the proposed model. Using previous research in this area, analytical and bootstrap estimators of the mean squared prediction error (MSPE) o...
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Introduction Multivariate Fay–Herriot models for estimating small area indicators are introduced. Among the available procedures for fitting linear mixed models, the residual maximum likelihood (REML) is employed. The empirical best predictor (EBLUP) of the vector of area means is derived. An approximation to the matrix of mean squared crossed prediction errors (MSE) is given and four MSE estim...
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ژورنال
عنوان ژورنال: Seminar Nasional Official Statistics
سال: 2020
ISSN: 2722-1970
DOI: 10.34123/semnasoffstat.v2019i1.185