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Statistical predictions with glmnet.


ABSTRACT: 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.

SUBMITTER: Engebretsen S 

PROVIDER: S-EPMC6708235 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Statistical predictions with glmnet.

Engebretsen Solveig S   Bohlin Jon J  

Clinical epigenetics 20190823 1


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. ...[more]

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