Gets all the data for the summary.gmwm function.
get_summary(theta, desc, objdesc, model_type, wv_empir, theo, scales, V,
omega, obj_value, N, alpha, robust, eff, inference, fullV, bs_gof,
bs_gof_p_ci, bs_theta_est, bs_ci, B)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
A vec that
A vec that
A mat that contains the V matrix used to obtain the GMWM.
A mat that
A double that contains the objective function value at the optimized solution.
A int that indicates how long the time series is.
A double that handles the alpha level of the confidence interval (1-alpha)*100
A bool that indicates whether the estimation should be robust or not.
A double that specifies the amount of efficiency required by the robust estimator.
A bool that indicates whether inference (e.g. GoF) should be run.
A bool that indicates whether the matrix has been fully bootstrapped.
A bool indicating whether the GoF should be bootstrapped or done asymptotically.
A bool indicating whether a bootstrapped p-value should be generated during the bootstrapped GoF
A bool that indicates whether a bootstrapped CI should be obtained or to use analytical derivatives.
A int that indicates how many iterations should take place.
A field<mat> that contains bootstrapped / asymptotic GoF results as well as CIs.