nested_optimization_wrapper: Helper-function - finds parameters minimizing log-likelihood...
In badp: Bayesian Averaging for Dynamic Panels

nested_optimization_wrapper

R Documentation

Helper-function - finds parameters minimizing log-likelihood function for the nested version of the SEM setup, using BFGS method

Description

Helper-function - finds parameters minimizing log-likelihood function for the nested version of the SEM setup, using BFGS method

Usage

nested_optimization_wrapper(
  params,
  df,
  timestamp_col,
  entity_col,
  dep_var_col,
  data,
  exact_value,
  init_value,
  max_init_attempts,
  control,
  max_restarts,
  restart_tol,
  max_reoptimizations
)

Arguments

`params`	Vector of the initial parameters
`df`	Data frame with data for the SEM analysis.
`timestamp_col`	Column which determines time periods. For now only natural numbers can be used as timestamps
`entity_col`	Column which determines entities (e.g. countries, people)
`dep_var_col`	Column with dependent variable
`data`	List of SEM setup matrices shared along the models
`exact_value`	Whether the exact value of the likelihood should be computed (`TRUE`) or just the proportional part (`FALSE`). Check sem_likelihood for details.
`init_value`	The generator function the starting point in `params` was drawn from, or a single number standing for the corresponding constant generator. It is used to redraw the starting point if the likelihood turns out to be undefined at the drawn point. See optim_model_space.
`max_init_attempts`	Maximum number of starting points drawn from `init_value` for this model. See optim_model_space.
`control`	a list of control parameters for the optimization which are passed to optim. Default is `list(trace = 0, maxit = 10000, fnscale = -1, REPORT = 100, scale = 0.05)`.
`max_restarts`	Maximum number of times the BFGS optimization is restarted from its previous solution for a single model. A restart resets the internal curvature approximation of BFGS, which often makes further progress on ill-conditioned likelihood ridges where a single run stalls. Default is `5`.
`restart_tol`	Log-likelihood improvement between restarts below which the optimization is considered converged. Improvements of this size are immaterial for posterior model probabilities. Default is `1e-3`.
`max_reoptimizations`	Maximum number of times this model is re-optimized from a fresh starting point when its solution turns out to be one no standard errors can be computed from. See optim_model_space.