Using the bootstrap approach, we simulate a model based on user supplied parameters, obtain the wavelet variance, and then V.
opt_n_gof_bootstrapper(theta, desc, objdesc, scales, model_type, N, robust,
eff, alpha, H)A vector 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> that contains an object description (e.g. values) of the model.
A vec containing the scales of the process.
A string containing the model type either: SSM or IMU
A int indicating how long the integer is.
A bool indicating robust (T) or classical (F).
A double that handles efficiency.
A int that indicates how many bootstraps should be obtained.
A vec that contains the parameter estimates from GMWM estimator.
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