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A simultaneous variable selection methodology for linear mixed models
Juming Pan, Junfeng Shang
Mathematics & Statistics
Research output
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Article
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peer-review
6
Scopus citations
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Dive into the research topics of 'A simultaneous variable selection methodology for linear mixed models'. Together they form a unique fingerprint.
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Keyphrases
Selection Strategy
100%
Linear Mixed Model
100%
Fixed Effects
100%
Random Effects
100%
Profile Log-likelihood
100%
Simulation Study
50%
Longitudinal Data
50%
Optimization Algorithm
50%
Log-likelihood Ratio
50%
Parameter Estimation
50%
Two-stage Procedure
50%
Computational Efficiency
50%
Real Data Applications
50%
Newton-Raphson Method
50%
Clustered Data
50%
Model Selection Consistency
50%
Selection Accuracy
50%
One-stage Procedure
50%
Sparse Selection
50%
Adaptive Penalty Function
50%
Mathematics
Linear Mixed Model
100%
Profile Log
100%
Random Effect
100%
Simulation Study
50%
Model Selection
50%
Newton-Raphson
50%
Log Likelihood
50%
Log Likelihood Function
50%
Clustered Data
50%
Longitudinal Data
50%
Parameter Estimation
50%
Real Data
50%