onlineVAR (version 0.1-1)

onlineVAR.control: Auxiliary Function for Controlling onlineVAR Fitting

Description

Auxiliary function for onlineVAR fitting.

Usage

onlineVAR.control(lambda.ratio = NULL, nlambda = NULL, 
  lambda.min.ratio = NULL, abstol = 0.001, trace = FALSE, start = NULL, 
  parallel = FALSE, predall = FALSE)

Arguments

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 and lambda.min.ratio. If supplied, nlambda and lambda.min.ratio are ignored.

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 abstol. Default is 0.001.

trace

If TRUE coefficient estimates are stored for all time steps. If FALSE coefficient matrices are only stored for the last time step to save memory.

start

Object of class "onlineVAR". Coefficient estimates from the last time step are used as staring values. Can be used to continue updating the model with new data.

parallel

If TRUE the model fitting for the different lambda is parallelized.

predall

Logical whether predictions from all penalization parameters in the sequence are stored.

Value

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.

See Also

onlineVAR