# Is standardizing data necessary for glasso?

I am wondering, if it is necessary to standardize data (mean zero and stddev eq. 1) for glasso. In many papers on glasso this is mentioned to have data with mean=0 and stddev 1, while using covarience matrix of the data for variable selection through glasso. However, in book "Using R! by Gentleman et al (Editors) covarience matrix is converted to correlation matrix and then glasso is applied without standardizing data.

Would appreciate explaination about it i.e. whether starndardization is necessary for glasso and if yes then why.

• I am not sure to follow: using the covariance of standardized variables is the same as using the correlation matrix, no?
– chl
Oct 8 '14 at 14:20
• What you have asked is a different question. My question is do we need to standardize data before glasso. In literature several papers say to have mean zero and covarience matrix sigma before running glasso. Several papers explicitly say to standardize data. However, in other places it is not done. Like in Book "USE R" Thibshirani is one of the authers and they don't normalize data before running glasso. Now I am confused do we need to starndize data or not? Oct 8 '14 at 14:24
• sorry authers are Søren Højsgaard, David Edwards et al and not Thibshirani Oct 8 '14 at 14:34

• I don't think so, but I don't have experience specifically with glasso. Try it both ways (on a data subset if there are issues with time/cost of computation) and see if it makes a difference.