grpl.control-class {grplasso} | R Documentation |
Class "grpl.control": Options for the Group Lasso Algorithm
Description
Objects of class "grpl.control" define options such as bounds on the Hessian,
convergence criteria and output management for the Group Lasso algorithm.
Details
For the convergence criteria see chapter 8.2.3.2 of Gill et
al. (1981).
Objects from the Class
Objects can be created by calls of the form grpl.control(...)
Slots
save.x
- a logical indicating whether the design matrix
should be saved.
save.y
- a logical indicating whether the response should
be saved.
update.hess
- should the hessian be updated in each
iteration ("always")? update.hess = "lambda" will update
the Hessian once for each component of the penalty
parameter "lambda" based on the parameter estimates
corresponding to the previous value of the penalty
parameter.
update.every
- Only used if update.hess = "lambda". E.g. set to 3
if you want to update the Hessian only every third grid point.
inner.loops
- How many loops should be done (at maximum)
when solving only the active set (without considering the remaining
predictors). Useful if the number of predictors is large. Set to 0
if no inner loops should be performed.
line.search
- Should line searches be performed?
max.iter
- Maximal number of loops through all groups
tol
- convergence tolerance; the smaller the more precise.
lower
- lower bound for the diagonal approximation of the
corresponding block submatrix of the Hessian of the negative
log-likelihood function.
upper
- upper bound for the diagonal approximation of the
corresponding block submatrix of the Hessian of the negative
log-likelihood function.
beta
- scaling factor β < 1 of the Armijo line search.
sigma
- 0 < σ < 1 used in the Armijo line search.
trace
- integer.
1
prints the current lambda value,
2
prints the improvement in the objective function after each
sweep through all the parameter groups and additional information.
References
Philip E. Gill, Walter Murray and Margaret H. Wright (1981)
Practical Optimization, Academic Press.
Dimitri P. Bertsekas (2003) Nonlinear Programming, Athena Scientific.
[Package
grplasso version 0.4-2
Index]