Statistical predictions with glmnet
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...
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| Veröffentlicht in: | Clinical epigenetics 2019-08, Vol.11 (1), p.123, Article 123 |
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| container_title | Clinical epigenetics |
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| creator | Engebretsen, Solveig Bohlin, Jon |
| description | 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. |
| doi_str_mv | 10.1186/s13148-019-0730-1 |
| format | Article |
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| identifier | ISSN: 1868-7075 |
| ispartof | Clinical epigenetics, 2019-08, Vol.11 (1), p.123, Article 123 |
| issn | 1868-7075 1868-7083 1868-7083 1868-7075 |
| language | eng |
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| source | NORA - Norwegian Open Research Archives; DOAJ Directory of Open Access Journals; SpringerNature Journals; PubMed Central Open Access; Springer Nature OA Free Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central |
| subjects | Analysis Bias Economic models Epidemiology Epigenetic inheritance Letter to the Editor Methods Public health Resveratrol Statistical prediction |
| title | Statistical predictions with glmnet |
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