Fit a model in which the fixed effects parameters are penalized. The dependence parameters are held fixed at their estimated values in the unpenalized model.
Parameters:  method : string of Penalty object
alpha : arraylike
ceps : positive real scalar
ptol : positive real scalar
maxit : integer
fit_kwargs : keywords


Returns:  A MixedLMResults instance containing the results. : 
Notes
The covariance structure is not updated as the fixed effects parameters are varied.
The algorithm used here for L1 regularization is a”shooting” or cyclic coordinate descent algorithm.
If method is ‘l1’, then fe_pen and cov_pen are used to obtain the covariance structure, but are ignored during the L1penalized fitting.
References
Friedman, J. H., Hastie, T. and Tibshirani, R. Regularized Paths for Generalized Linear Models via Coordinate Descent. Journal of Statistical Software, 33(1) (2008) http://www.jstatsoft.org/v33/i01/paper
http://statweb.stanford.edu/~tibs/stat315a/Supplements/fuse.pdf