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Mixed Effects Prediction under Benchmarking and Applications to Small Area Estimation
http://hdl.handle.net/2261/50230
http://hdl.handle.net/2261/502306df71955-debd-4b75-8978-e264e8276c66
Item type | テクニカルレポート / Technical Report(1) | |||||
---|---|---|---|---|---|---|
公開日 | 2013-05-31 | |||||
タイトル | ||||||
タイトル | Mixed Effects Prediction under Benchmarking and Applications to Small Area Estimation | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題 | Benchmarking | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | best linear unbiased predictor | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | constrained Bayes | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | empirical Bayes | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | linear mixed model | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | mean squared error | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | parametric bootstrap | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | second-order approximation | |||||
主題Scheme | Other | |||||
キーワード | ||||||
主題 | small area estimation | |||||
主題Scheme | Other | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_18gh | |||||
タイプ | technical report | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
Kubokawa, Tatsuya
× Kubokawa, Tatsuya |
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著者所属 | ||||||
著者所属 | Department of Economics, University of Tokyo | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | The empirical best linear unbiased predictor (EBLUP) in the linear mixed model (LMM) is useful for the small area estimation in the sense of increasing the precision of estimation of small area means. However, one potential difficulty of EBLUP is that when aggregated, the overall estimate for a larger geographical area may be quite different from the corresponding direct estimate like the overall sample mean. One way to solve this problem is the benchmarking approach, and the constrained EBLUP is a feasible solution which satisfies the constraints that the aggregated mean and variance are identical to the requested values of mean and variance. An interesting query is whether the constrained EBLUP may have a larger estimation error than EBLUP. In this paper, we address this issue by deriving asymptotic approximations of MSE of the constrained EBLUP. Also, we provide asymptotic unbiased estimators of the MSE of the constrained EBLUP based on the parametric bootstrap method, and establish their second-order justification. Finally, the performances of the suggested MSE estimators are numerically investigated. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 本文フィルはリンク先を参照のこと | |||||
書誌情報 |
Discussion paper series. CIRJE-F 巻 CIRJE-F-832, 発行日 2012-01 |
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書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA11450569 | |||||
フォーマット | ||||||
内容記述タイプ | Other | |||||
内容記述 | application/pdf | |||||
日本十進分類法 | ||||||
主題 | 335 | |||||
主題Scheme | NDC | |||||
出版者 | ||||||
出版者 | 日本経済国際共同センター | |||||
出版者別名 | ||||||
Center for International Research on the Japanese Economy | ||||||
関係URI | ||||||
識別子タイプ | URI | |||||
関連識別子 | http://www.cirje.e.u-tokyo.ac.jp/research/dp/2012/2012cf832ab.html |