get_initial_values: Initialization of numerical likelihood optimization
In fHMM: Fitting Hidden Markov Models to Financial Data

get_initial_values

R Documentation

Initialization of numerical likelihood optimization

This helper function generates a set of initial values for the numerical optimization of the model likelihood function.

get_initial_values(
  data,
  ncluster = 1,
  seed = NULL,
  verbose = TRUE,
  initial_estimate = NULL
)

`data`	[`fHMM_data`] An object of class `fHMM_data`.
`ncluster`	[`integer(1)`] Set the number of clusters for parallel optimization runs to reduce optimization time. By default, `ncluster = 1` (no clustering).
`seed`	[`NULL` \| `integer(1)`] Set a seed for the generation of initial values. No seed by default.
`verbose`	[`logical(1)`] Set to `TRUE` to print progress messages.
`initial_estimate`	[`NULL` \| `parUncon`] Optionally defines an initial estimate for the numerical likelihood optimization. Good initial estimates can improve the optimization process. Can be: `NULL` (the default), in this case applies a heuristic to calculate a good initial estimate or uses the true parameter values (if available and `data$controls$origin` is `TRUE`) or an object of class `parUncon` (i.e., a `numeric` of unconstrained model parameters), for example the estimate of a previously fitted model (i.e. the element `model$estimate`).