dot-gpOptimizationInternal: .gpOptimizationInternal
In lessSEM: Non-Smooth Regularization for Structural Equation Models

.gpOptimizationInternal

R Documentation

.gpOptimizationInternal

Description

Internal function: This function computes the regularized models for all penaltiy functions which are implemented for glmnet and gist. Use the dedicated penalty functions (e.g., lessSEM::gpLasso) to penalize the model.

Usage

.gpOptimizationInternal(
  par,
  weights,
  fn,
  gr = NULL,
  additionalArguments,
  isCpp = FALSE,
  penalty,
  tuningParameters,
  method,
  control
)

Arguments

`par`	labeled vector with starting values
`weights`	labeled vector with weights for each of the parameters in the model.
`fn`	R function which takes the parameters AND their labels as input and returns the fit value (a single value)
`gr`	R function which takes the parameters AND their labels as input and returns the gradients of the objective function. If set to NULL, numDeriv will be used to approximate the gradients
`additionalArguments`	additional argument passed to fn and gr
`isCpp`	boolean: are fn and gr C++ function pointers?
`penalty`	string: name of the penalty used in the model
`tuningParameters`	data.frame with tuning parameter values
`method`	which optimizer should be used? Currently implemented are ista and glmnet. With ista, the control argument can be used to switch to related procedures (currently gist).
`control`	used to control the optimizer. This element is generated with the controlIsta() and controlGlmnet() functions.