parameter.anneal: Parameter Search using Simulated Annealing

In tbrycekelly/TheSource: TheSource: It Will Hold Your Beer

Parameter Search using Simulated Annealing

Usage

parameter.anneal(
  n,
  cost,
  ...,
  bounds,
  progression = NULL,
  max.iter = 1e+06,
  k = 2
)

Arguments

n	Number of accepted solutions to seek
cost	The cost function which must return a numeric value and accept parameter values as the first arguments and in the order they are provided.
...	Optional argument that is passed directly onto the cost function
bounds	A dataframe containing the minimum and maximum values permitted of each parameter
progression	The step length for each parameter (default is 1 \item max.iterThe maximum number of steps to take before returning (even if n is unsatisfied). **Goal for function to return via n rather than by max.iter. \item kThe cooling coefficent. Larger values imply higher initial "temperature" and easier solution acceptance.

Implements an MCMC algorithm (simulated annealing) to determine a global optimum from within the stated bounds. Thomas Bryce Kelly

tbrycekelly/TheSource documentation built on Nov. 7, 2023, 12:48 a.m.