xrnet_control {xrnet}

Control function for xrnet fitting

Description

Control function for xrnet fitting.

Usage

xrnet_control(
  tolerance = 1e-08,
  max_iterations = 1e+05,
  dfmax = NULL,
  pmax = NULL,
  lower_limits = NULL,
  upper_limits = NULL
)

Arguments

tolerance

positive convergence criterion. Default is 1e-08.

max_iterations

maximum number of iterations to run coordinate gradient descent across all penalties before returning an error. Default is 1e+05.

dfmax

maximum number of variables allowed in model. Default is ncol(x) + ncol(unpen) + ncol(external) + intercept[1] + intercept[2].

pmax

maximum number of variables with nonzero coefficient estimate. Default is min(2 * dfmax + 20, ncol(x) + ncol(unpen) + ncol(external) + intercept[2]).

lower_limits

vector of lower limits for each coefficient. Default is -Inf for all variables.

upper_limits

vector of upper limits for each coefficient. Default is Inf for all variables.

Value

A list object with the following components:

tolerance

The coordinate descent stopping criterion.

dfmax

The maximum number of variables that will be allowed in the model.

pmax

The maximum number of variables with nonzero coefficient estimate.

lower_limits

Feature-specific numeric vector of lower bounds for coefficient estimates

upper_limits

Feature-specific numeric vector of upper bounds for coefficient estimates