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A Minimax Two-Sample Test for Functional Data via Grothendieck's Divergence.

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Title: A Minimax Two-Sample Test for Functional Data via Grothendieck's Divergence.
Authors: Chen, Yan1 (AUTHOR), Lin, Hongmei2 (AUTHOR), Wang, Xueqin3 (AUTHOR), Wen, Canhong3 (AUTHOR) wench@ustc.edu.cn
Source: Journal of the American Statistical Association. Mar2026, Vol. 121 Issue 553, p612-623. 12p.
Database: Business Source Ultimate
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An: 193014974
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  Data: A Minimax Two-Sample Test for Functional Data via Grothendieck's Divergence.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+the+American+Statistical+Association%22">Journal of the American Statistical Association</searchLink>. Mar2026, Vol. 121 Issue 553, p612-623. 12p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=193014974
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/01621459.2025.2537455
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 612
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      – TitleFull: A Minimax Two-Sample Test for Functional Data via Grothendieck's Divergence.
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            NameFull: Chen, Yan
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            NameFull: Lin, Hongmei
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            NameFull: Wang, Xueqin
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            – D: 01
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              Text: Mar2026
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              Y: 2026
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              Value: 121
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              Value: 553
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