Statistical predictions with glmnet
Norwegian Institute of Public Health · University of Oslo · +1 more institution
Indexed incrossrefdoaj
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.
Citation impact
1,239
total citations
- FWCI
- 29.82
- Percentile
- 100%
- References
- 28
Citations per year
Authors
2Topics & keywords
Topics
Keywords
- Epigenome
- Mean squared error
- Statistics
- Variance (accounting)
- Regression
- Elastic net regularization
- Regression analysis
- Econometrics
No related works found for this paper.