calibrater: Calibration of Decision-Analytic Models

summ_optim

R Documentation

Summarise and/or create uncertainty estimates from the hessian matrix

Description

Summarise and/or create uncertainty estimates from the hessian matrix

Usage

summ_optim(
  .params_name = v_params_names,
  .params_vals,
  .gof = NULL,
  .gof_name,
  .gof_value,
  .s_method,
  .par,
  .func = NULL,
  .args = NULL,
  .hessian = NULL,
  .maximiser = TRUE,
  .convergence,
  .trace = NULL,
  ...
)

Arguments

`.params_name`	Character vector containing the names of the parameters that were passed to the goodness-of-fit algorithm or will be passed to .func.
`.params_vals`	Guess or initial values used to start the algorithm.
`.gof`	goodness-of-fit function used or to be used in the optimisation.
`.gof_name`	Character naming goodness-of-fit method that produced samples
`.gof_value`	Numeric goodness-of-fit value for the corresponding parameters.
`.s_method`	Character naming search algorithm that produced .GoF_value.
`.par`	Parameter values to be used to generate `95 interval` and/or passed to .func to generate the .hessian matrix.
`.func`	A function passed to and to be optimised by .gof.
`.args`	A list of arguments passed to .func.
`.hessian`	The hessian matrix.
`.maximiser`	Logical for whether algorithm that created (or .func which will create) the hessian matrix maximised the goodness-of-fit function. Default is `TRUE`.
`.convergence`	Convergence label; 0 successful convergence
`.trace`	Optimisation function trace
`...`	Extra arguments to be passed to .gof.