grpregOverlap (version 2.2-0)

grpregOverlap-package: Penalized regression models with overlapping grouped variables.

Description

This package fits regularization paths for linear, logistic or poisson regression models with overlapping grouped variables. The idea of the latent group lasso penalty (Jacob et al., 2009) is implemented and extended to group MCP, and group SCAD for overlapping group selection.

Details

The package is built upon the R package grpreg by Dr. Patrick Breheny. The following functions are documented in the help pages:

• expandX
• overlapMatrix
• incidenceMatrix
• grpregOverlap
• cv.grpregOverlap
• plot.grpregOverlap
• predict.grpregOverlap
• select.grpregOverlap
• summary.cv.grpregOverlap

The following data sets are documented in the help pages:

• pathway.dat

References

• Zeng, Y., and Breheny, P. (2016). Overlapping Group Logistic Regression with Applications to Genetic Pathway Selection. Cancer Informatics, 15, 179-187. http://doi.org/10.4137/CIN.S40043.
• Jacob, L., Obozinski, G., and Vert, J. P. (2009, June). Group lasso with overlap and graph lasso. In Proceedings of the 26th annual international conference on machine learning, ACM: 433-440. http://www.machinelearning.org/archive/icml2009/papers/471.pdf
• Obozinski, G., Jacob, L., and Vert, J. P. (2011). Group lasso with overlaps: the latent group lasso approach. http://arxiv.org/abs/1110.0413.
• Breheny, P. and Huang, J. (2009) Penalized methods for bi-level variable selection. Statistics and its interface, 2: 369-380. http://myweb.uiowa.edu/pbreheny/publications/Breheny2009.pdf
• Huang J., Breheny, P. and Ma, S. (2012). A selective review of group selection in high dimensional models. Statistical Science, 27: 481-499. http://myweb.uiowa.edu/pbreheny/publications/Huang2012.pdf
• Breheny P and Huang J (2015). Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors. Statistics and Computing, 25: 173-187.http://myweb.uiowa.edu/pbreheny/publications/group-computing.pdf
• Breheny P and Huang J (2009). Penalized methods for bi-level variable selection. Statistics and Its Interface, 2: 369-380. http://myweb.uiowa.edu/pbreheny/publications/Breheny2009.pdf
• Breheny P (2014). R package 'grpreg'. https://CRAN.R-project.org/package=grpreg/grpreg.pdf
• Subramanian, et al. (2005). Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America, 102(43), 15545-15550. http://www.pnas.org/content/102/43/15545.short

Examples

## see examples in grpregOverlap