Rcfgl: rapid condition adaptive fused graphical lasso and application to modeling brain region co-expression networks

HIGHLIGHTS

• who: Souvik Seal and colleagues from the Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado have published the Article: RCFGL: Rapid Condition adaptive Fused Graphical Lasso and application to modeling brain region co-expression networks, in the Journal: (JOURNAL) of November/24,/2022
• what: The authors propose a faster alternative of CFGL named graphical lasso (RCFGL). The authors demonstrate the computational advantage and superior performance of the method compared to two methods FGL and FMGL and one method CFGL in both simulation study and real data analysis. In this paper . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.