Description Usage Arguments Value See Also
Auxiliary function for onlineVAR
fitting.
1 2 3 |
lambda.ratio |
Vector of penalization parameters as fractions of the
minimum lambda for which all coefficients are zero. If not specified
a sequence of lambda values is generated based on |
nlambda |
Number of lasso penalization parameters lambda. Default is 10. |
lambda.min.ratio |
Smallest value of lambda.ratio. Default is 0.0001 |
abstol |
Absolute tolerance for coordinate descent convergence.
In each time step the algorithm stops when the sum of coefficient estimates
does not change more than |
trace |
If |
start |
Object of class |
parallel |
If |
predall |
Logical whether predictions from all penalization parameters in the sequence are stored. |
An list of components named as the arguments.
nlambda |
Number of lasso penalization parameters in the lambda sequence. |
lambda.min.ratio |
Smallest value for lambda.ratio. |
abs.tol |
Absolute tolerance for coordinate descent convergence. |
lambda.ratio |
Lambda sequence as fractions of the minimum lambda for which all coefficients are zero. |
trace |
Logical whether coefficients should be stored for all time steps. |
start |
Starting values. |
parallel |
Logical whether the model fitting for the different lambda is parallelized. |
predall |
Logical whether prediction from all penalization parameters in the sequence are stored. |
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