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Parametric Transformed Fay-Herriot Model for Small Area Estimation
http://hdl.handle.net/2261/55621
http://hdl.handle.net/2261/556219508f38d-1b9e-4c67-87ff-f217dccb4568
| Item type | テクニカルレポート / Technical Report(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2014-01-16 | |||||
| タイトル | ||||||
| タイトル | Parametric Transformed Fay-Herriot Model for Small Area Estimation | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Asymptotically unbiased estimator | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Box-Cox transformation | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | dual power transformation | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Fay-Herriot model | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | linear mixed model | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | mean squared error | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | parametric bootstrap | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | small area estimation | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | variable selection | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||
| 資源タイプ | 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 |
Sugawara, Shonosuke
× Sugawara, Shonosuke× Kubokawa, Tatsuya |
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| 著者所属 | ||||||
| 値 | Graduate School of Economics, University of Tokyo | |||||
| 著者所属 | ||||||
| 値 | Faculty of Economics, University of Tokyo | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Consider the small area estimation when positive area-level data like income, revenue, harvests or production are available. Although a conventional method is the log-transformed 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 parameter is not consistent and that the transformed data are truncated. In this paper, we consider parametric transformed Fay-Herriot models, and clarify conditions on transformations under which the ML estimator of the transformation is consistent. It is shown that the dual power transformation satisfies the conditions. Based on asymptotic properties for estimators of parameters, we derive a second-order approximation of the prediction error of the empirical best linear unbiased predictors (EBLUP) and obtain a second-order unbiased estimator of the prediction error. Finally, performances of the proposed procedures are investigated through simulation and empirical studies. | |||||
| 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-911, 発行日 2013-12 |
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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 | |||||
| 出版者 | ||||||
| 出版者 | 日本経済国際共同センター | |||||
| 出版者別名 | ||||||
| 値 | 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/2013/2013cf911ab.html | |||||
