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  1. 論文誌(トランザクション)
  2. 数理モデル化と応用(TOM)
  3. Vol.17
  4. No.2

Multi-target Tobit Models for Completing Water Quality Data

https://ipsj.ixsq.nii.ac.jp/records/233712
https://ipsj.ixsq.nii.ac.jp/records/233712
12e955ac-1fbd-47d7-89ef-2ff4d23c5198
名前 / ファイル ライセンス アクション
IPSJ-TOM1702004.pdf IPSJ-TOM1702004.pdf (709.2 kB)
 2026年3月25日からダウンロード可能です。
Copyright (c) 2024 by the Information Processing Society of Japan
非会員:¥660, IPSJ:学会員:¥330, MPS:会員:¥0, DLIB:会員:¥0
Item type Trans(1)
公開日 2024-03-25
タイトル
タイトル Multi-target Tobit Models for Completing Water Quality Data
タイトル
言語 en
タイトル Multi-target Tobit Models for Completing Water Quality Data
言語
言語 eng
キーワード
主題Scheme Other
主題 [オリジナル論文] water quality data, censoring, data imputation, Tobit model, probabilistic model, linear regression
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
著者所属
Graduate School of Science and Technology, Gunma University
著者所属
Department of Civil and Environmental Engineering, Tohoku University
著者所属
The University of Tokyo
著者所属
Graduate School of Science and Technology, Gunma University
著者所属(英)
en
Graduate School of Science and Technology, Gunma University
著者所属(英)
en
Department of Civil and Environmental Engineering, Tohoku University
著者所属(英)
en
The University of Tokyo
著者所属(英)
en
Graduate School of Science and Technology, Gunma University
著者名 Yuya, Takada

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Yuya, Takada

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Daisuke, Sano

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Daisuke, Sano

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Syun-suke, Kadoya

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Syun-suke, Kadoya

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Tsuyoshi, Kato

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Tsuyoshi, Kato

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著者名(英) Yuya, Takada

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Daisuke, Sano

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Syun-suke, Kadoya

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Tsuyoshi, Kato

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論文抄録
内容記述タイプ Other
内容記述 Monitoring microbiological behaviors in water is crucial to manage public health risk from waterborne pathogens, although quantifying the concentrations of microbiological organisms in water is still challenging because concentrations of many pathogens in water samples may often be below the quantification limit, producing censoring data. To enable statistical analysis based on quantitative values, the true values of non-detected measurements are required to be estimated with high precision. Tobit model is a well-known linear regression model for analyzing censored data. One drawback of the Tobit model is that only the target variable is allowed to be censored. In this study, we devised a novel extension of the classical Tobit model, called the multi-target Tobit model, to handle multiple censored variables simultaneously by introducing multiple target variables. For fitting the new model, a numerical stable optimization algorithm was developed based on elaborate theories. Experiments conducted using several real-world water quality datasets provided an evidence that estimating multiple columns jointly gains a great advantage over estimating them separately.
論文抄録(英)
内容記述タイプ Other
内容記述 Monitoring microbiological behaviors in water is crucial to manage public health risk from waterborne pathogens, although quantifying the concentrations of microbiological organisms in water is still challenging because concentrations of many pathogens in water samples may often be below the quantification limit, producing censoring data. To enable statistical analysis based on quantitative values, the true values of non-detected measurements are required to be estimated with high precision. Tobit model is a well-known linear regression model for analyzing censored data. One drawback of the Tobit model is that only the target variable is allowed to be censored. In this study, we devised a novel extension of the classical Tobit model, called the multi-target Tobit model, to handle multiple censored variables simultaneously by introducing multiple target variables. For fitting the new model, a numerical stable optimization algorithm was developed based on elaborate theories. Experiments conducted using several real-world water quality datasets provided an evidence that estimating multiple columns jointly gains a great advantage over estimating them separately.
書誌レコードID
収録物識別子タイプ NCID
収録物識別子 AA11464803
書誌情報 情報処理学会論文誌数理モデル化と応用(TOM)

巻 17, 号 2, p. 21-29, 発行日 2024-03-25
ISSN
収録物識別子タイプ ISSN
収録物識別子 1882-7780
出版者
言語 ja
出版者 情報処理学会
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