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Bayesian binary quantile regression adaptive Lasso for modelling hypertension: a bootstrap based consistency analysis.

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Title: Bayesian binary quantile regression adaptive Lasso for modelling hypertension: a bootstrap based consistency analysis.
Authors: Hasibuan, Lilis Harianti1,2 (AUTHOR), Yanuar, Ferra1 (AUTHOR) ferrayanuar@sci.unand.ac.id, Devianto, Dodi1 (AUTHOR), Maiyastri1 (AUTHOR)
Source: Communications in Statistics: Case Studies & Data Analysis. Jun2026, p1-24. 24p. 2 Illustrations.
Database: Business Source Ultimate
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PubType: Academic Journal
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  Data: <searchLink fieldCode="JN" term="%22Communications+in+Statistics%3A+Case+Studies+%26+Data+Analysis%22">Communications in Statistics: Case Studies & Data Analysis</searchLink>. Jun2026, p1-24. 24p. 2 Illustrations.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=194837279
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      – Type: doi
        Value: 10.1080/23737484.2026.2671866
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      – Code: eng
        Text: English
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        PageCount: 24
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      – TitleFull: Bayesian binary quantile regression adaptive Lasso for modelling hypertension: a bootstrap based consistency analysis.
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            NameFull: Hasibuan, Lilis Harianti
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            NameFull: Yanuar, Ferra
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            NameFull: Devianto, Dodi
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            – D: 22
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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