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Statistical predictions with glmnet
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Journal Article
Statistical predictions with glmnet
2019
Overview
Elastic net type regression methods have become very popular for prediction of certain outcomes in epigenome-wide association studies (EWAS). The methods considered accept biased coefficient estimates in return for lower variance thus obtaining improved prediction accuracy. We provide guidelines on how to obtain parsimonious models with low mean squared error and include easy to follow walk-through examples for each step in R.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V
