Estimate Copula Parameters with Weighted Likelihood — estimate_copula_parameters

Estimates copula correlation parameters using weighted maximum likelihood. This function handles the copula-specific transformation from standardized residuals to uniform margins before applying the DCC-style correlation dynamics.

Usage

estimate_copula_parameters_weighted(
  residuals,
  weights,
  garch_pars,
  dcc_start_pars,
  dist_start_pars,
  spec,
  transformation = "parametric",
  copula_dist = "mvn",
  dynamics = "dcc",
  diagnostics = NULL,
  iteration = NULL,
  state = NULL,
  verbose = FALSE
)

Arguments

residuals: T x k matrix of residuals
weights: T-vector of observation weights
garch_pars: List of GARCH parameters per series
dcc_start_pars: Named list of starting DCC parameters
dist_start_pars: Named list of distribution parameters (e.g., shape)
spec: Model specification list
transformation: Type of PIT transformation ("parametric", "empirical", "spd")
copula_dist: Copula distribution ("mvn" or "mvt")
diagnostics: Diagnostics object (optional)
iteration: Current EM iteration (optional)
state: Current regime state (optional)
verbose: Logical; print diagnostic information

Value

List with dcc_pars, dist_pars, weighted_ll, warnings, diagnostics