2021
DOI: 10.3390/e23101348
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Sparse Estimation Strategies in Linear Mixed Effect Models for High-Dimensional Data Application

Abstract: In a host of business applications, biomedical and epidemiological studies, the problem of multicollinearity among predictor variables is a frequent issue in longitudinal data analysis for linear mixed models (LMM). We consider an efficient estimation strategy for high-dimensional data application, where the dimensions of the parameters are larger than the number of observations. In this paper, we are interested in estimating the fixed effects parameters of the LMM when it is assumed that some prior informatio… Show more

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Cited by 2 publications
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References 25 publications
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