کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
417214 681468 2008 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Analytic and bootstrap approximations of prediction errors under a multivariate Fay–Herriot model
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Analytic and bootstrap approximations of prediction errors under a multivariate Fay–Herriot model
چکیده انگلیسی

The prediction of vectors of small area quantities based on a multivariate Fay–Herriot model is addressed. For this, an empirical best linear unbiased predictor (EBLUP) of the target vector is used, where the model parameters are estimated by two different methods based on moments. The mean cross product error matrix of the multidimensional EBLUP is approximated both analytically and by a wild bootstrap method that yields direct and bias-corrected bootstrap estimators. A simulation study compares the small sample properties of the bootstrap estimators and the analytical approximation, including a comparison under lack of normality. Finally, the number of replicates needed for the bootstrap procedures to get stabilized are studied.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 52, Issue 12, 15 August 2008, Pages 5242–5252
نویسندگان
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