A Necessary Condition for Semiparametric Efficiency of Experimental Designs

Hisatoshi Tanaka*

*この研究の対応する著者

研究成果: Conference contribution

抄録

The efficiency of estimation depends not only on the method of estimation but also on the distribution of data. In statistical experiments, statisticians can at least partially design the data-generating process to obtain high estimation performance. This paper proposes a necessary condition for a semiparametrically efficient experimental design. We derived a formula to determine the efficient distribution of the input variables. The paper also presents an application to the optimal bid design problem of contingent valuation survey experiments.

本文言語English
ホスト出版物のタイトルGeometric Science of Information - 5th International Conference, GSI 2021, Proceedings
編集者Frank Nielsen, Frédéric Barbaresco
出版社Springer Science and Business Media Deutschland GmbH
ページ718-725
ページ数8
ISBN(印刷版)9783030802080
DOI
出版ステータスPublished - 2021
イベント5th International Conference on Geometric Science of Information, GSI 2021 - Paris, France
継続期間: 2021 7月 212021 7月 23

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12829 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference5th International Conference on Geometric Science of Information, GSI 2021
国/地域France
CityParis
Period21/7/2121/7/23

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

フィンガープリント

「A Necessary Condition for Semiparametric Efficiency of Experimental Designs」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル