Journal ArticleOPEN ACCESS

Analysis of Penalized Regression Methods in a Simple Linear Model on the High-Dimensional Data

  • Zari Farhadi Z
  • Arabi Belaghi R
  • Gurunlu Alma O
American Journal of Theoretical and Applied Statistics (2019) 8(5) 185
DOI: 10.11648/j.ajtas.20190805.14
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Abstract

Shrinkage methods for linear regression were developed over the last ten years to reduce the weakness of ordinary least squares (OLS) regression with respect to prediction accuracy. And, high dimensional data are quickly growing in many areas due to the …

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APA

Zari Farhadi, Z. F., Arabi Belaghi, R., & Gurunlu Alma, O. (2019). Analysis of Penalized Regression Methods in a Simple Linear Model on the High-Dimensional Data. American Journal of Theoretical and Applied Statistics, 8(5), 185. https://doi.org/10.11648/j.ajtas.20190805.14

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