Statistical predictions with glmnet
S Engebretsen, J Bohlin - Clinical epigenetics, 2019 - Springer
S Engebretsen, J Bohlin
Clinical epigenetics, 2019•SpringerElastic 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.
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.
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.
Springer
