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For: Wang Z, Wang H, Wang S. Linear mixed-effects model for multivariate longitudinal compositional data. Neurocomputing 2019;335:48-58. [DOI: 10.1016/j.neucom.2019.01.043] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Number Cited by Other Article(s)
1
Sun H, Liu Q. Robust variable selection in semiparametric mixed effects longitudinal data models. COMMUN STAT-THEOR M 2022. [DOI: 10.1080/03610926.2022.2100421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
2
Alenazi A. A review of compositional data analysis and recent advances. COMMUN STAT-THEOR M 2021. [DOI: 10.1080/03610926.2021.2014890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
3
Wang X, Wang H, Wang S, Yuan J. Convex clustering method for compositional data via sparse group lasso. Neurocomputing 2021. [DOI: 10.1016/j.neucom.2020.10.105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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