A Note on the Evidence Approximation in Bayesian Experimental Design Models Based on an Orthonormal System

• Ukita Yoshifumi

  Yokohama College of Commerce

抄録

In this paper, we first present a theorem on the relationship between the traditional model and a model based on an orthonormal system in experimental design. Using the theorem, the former model can be converted to the latter, and vice versa. Next, we introduce prior distributions over the hyperparameters for experimental design models to consider fully Bayesian predictions. Combining the conversion and a previous result, we show that we can make an approximation in which we set the hyperparameters to specific values determined by maximizing the evidence function.

収録刊行物

• 信号処理

  信号処理 22 (6), 307-314, 2018-11-25

  信号処理学会

キーワード

• evidence approximation
• experimental design
• linear model
• Bayesian machine learning
• orthonormal system
• Fourier analysis

詳細情報

• CRID: 1390564238048412032
• NII論文ID: 130007521379
• DOI: 10.2299/jsp.22.307
• ISSN: 18801013
• ISSN: 13426230
• Web Site: https://www.jstage.jst.go.jp/article/jsp/22/6/22_307/_pdf
• 本文言語コード: en
• データソース種別:
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  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可