If you use any of the L2-norm penalties (penalty='grLasso', 'grMCP', or 'grSCAD'), cite the Statistics and Computing article. If you use the group exponential lasso (penalty='gel'), cite the Biometrics article. If you use the composite MCP (penalty='cMCP') or group bridge penalties, cite the Statistics and its Interface (2009) article; note that the penalty is referred to as the 'group MCP' in the original article, but it would be better to refer to it as 'composite MCP' in future works.

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.

Breheny P (2015). The group exponential lasso for bi-level variable selection. Biometrics, 71: 731-740.

Breheny, P. and Huang, J. (2009) Penalized methods for bi-level variable selection. Statistics and its interface, 2: 369-380.

Corresponding BibTeX entries:

@Article{, author = {Patrick Breheny and Jian Huang}, title = {Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors}, journal = {Statistics and Computing}, year = {2015}, volume = {25}, pages = {173-187}, }

@Article{, author = {Patrick Breheny}, title = {The group exponential lasso for bi-level variable selection}, year = {2015}, journal = {Biometrics}, volume = {71}, pages = {731-740}, }

@Article{, author = {Patrick Breheny and Jian Huang}, title = {Penalized methods for bi-level variable selection.}, journal = {Statistics and its interface}, year = {2009}, volume = {2}, pages = {369-380}, }