This function uses information obtained previously (e.g. WV covariance matrix) to re-estimate a different model parameterization
gmwm_update_cpp(theta, desc, objdesc, model_type, N, expect_diff, ranged,
orgV, scales, wv, starting, compute_v, K, H, G, robust, eff)A vec with dimensions N x 1 that contains user-supplied initial values for parameters
A vector<string> indicating the models that should be considered.
A field<vec> containing a list of parameters (e.g. AR(1) = c(1,1), ARMA(p,q) = c(p,q,1))
A string that represents the model transformation
A vec that contains the scales or taus (2^(1:J))
A bool that indicates whether we guessed starting (T) or the user supplied estimates (F).
A vec that contains the empirical wavelet variance
A mat that represents the covariance matrix.
A field<mat> that contains the parameter estimates from GMWM estimator.
Wavelet variance based estimation for composite stochastic processes, S. Guerrier and Robust Inference for Time Series Models: a Wavelet-Based Framework, S. Guerrier