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Parametric Bootstrap Methods for Bias Correction in Linear Mixed Models
http://hdl.handle.net/2261/50208
http://hdl.handle.net/2261/50208c0cef1d7-a377-4dab-ad93-2ce8e93aa3f6
Item type | テクニカルレポート / Technical Report(1) | |||||
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公開日 | 2017-01-17 | |||||
タイトル | ||||||
タイトル | Parametric Bootstrap Methods for Bias Correction in Linear Mixed Models | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Best linear unbiased predictor | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | confidence interval | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | empirical Bayes procedure | |||||
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 | second-order correction | |||||
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 | maximum likelihood estimator | |||||
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 | nested error regression model | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | parametric bootstrap | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | restricted maximum likelihood estimator | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | small area estimation | |||||
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 |
Kubokawa, Tatsuya
× Kubokawa, Tatsuya× Nagashima, Bui |
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著者所属 | ||||||
値 | Faculty of Economics, University of Tokyo | |||||
著者所属 | ||||||
値 | Graduate School in 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, and the estimation of the mean squared error (MSE) of EBLUP is important as a measure of uncertainty of EBLUP. To obtain a second-order unbiased estimator of the MSE, the second-order bias correction has been derived mainly based on Taylor series expansions. However, this approach is harder to implement in complicated models with more unknown parameters like variance components, since we need to compute asymptotic bias, variance and covariance for estimators of unknown parameters as well as partial derivatives of some quantities. The same difficulty occurs in construction of confidence intervals based on EBLUP with second-order correction and in derivation of second-order bias correction terms in the Akaike Information Criterion (AIC) and the conditional AIC. To avoid such difficulty in derivation of second-order bias correction in these problems, the parametric bootstrap methods are suggested in this paper, and their second-order justifications are established. Finally, performances of the suggested procedures are numerically investigated in comparison with some existing procedures given in the literature. | |||||
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-801, 発行日 2011-04 |
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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Scheme | NDC | |||||
主題 | 335 | |||||
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/2011/2011cf801ab.html | |||||
異版あり | ||||||
関連タイプ | hasVersion | |||||
識別子タイプ | URI | |||||
関連識別子 | http://doi.org/10.1016/j.jmva.2011.12.002 |