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BioMed Research International
Volume 2015 (2015), Article ID 143712, 18 pages
http://dx.doi.org/10.1155/2015/143712
Review Article

The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

1Erasmus University Rotterdam Institute for Behavior and Biology, Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Postbus 1738, 3000 DR Rotterdam, Netherlands
2Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Postbus 1738, 3000 DR Rotterdam, Netherlands

Received 28 November 2014; Accepted 24 December 2014

Academic Editor: Junwen Wang

Copyright © 2015 Ronald de Vlaming and Patrick J. F. Groenen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [4 citations]

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  • Yu-Ru Su, Chong-Zhi Di, and Li Hsu, “A unified powerful set-based test for sequencing data analysis of GxE interactions,” Biostatistics, pp. kxw034, 2016. View at Publisher · View at Google Scholar
  • Cornelius A. Rietveld, and Dinand Webbink, “On the genetic bias of the quarter of birth instrument,” Economics and Human Biology, vol. 21, pp. 137–146, 2016. View at Publisher · View at Google Scholar
  • Mauricio Mazo Lopera, Brandon Coombes, and Mariza de Andrade, “An Efficient Test for Gene-Environment Interaction in Generalized Linear Mixed Models with Family Data,” International Journal of Environmental Research and Public Health, vol. 14, no. 10, pp. 1134, 2017. View at Publisher · View at Google Scholar
  • Inga Schwabe, Luc Janss, and Stéphanie M. van den Berg, “Can We Validate the Results of Twin Studies? A Census-Based Study on the Heritability of Educational Achievement,” Frontiers in Genetics, vol. 8, 2017. View at Publisher · View at Google Scholar