get_summary: Routing function for summary info
In gmwm: Generalized Method of Wavelet Moments

Gets all the data for the summary.gmwm function.

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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)

`theta`	A `vec` with dimensions N x 1 that contains user-supplied initial values for parameters
`desc`	A `vector<string>` indicating the models that should be considered.
`objdesc`	A `field<vec>` containing a list of parameters (e.g. AR(1) = c(1,1), ARMA(p,q) = c(p,q,1))
`model_type`	A `string` that represents the model transformation
`wv_empir`	A `vec` that
`theo`	A `vec` that
`scales`	A `vec` that
`V`	A `mat` that contains the V matrix used to obtain the GMWM.
`omega`	A `mat` that
`obj_value`	A `double` that contains the objective function value at the optimized solution.
`N`	A `int` that indicates how long the time series is.
`alpha`	A `double` that handles the alpha level of the confidence interval (1-alpha)*100
`robust`	A `bool` that indicates whether the estimation should be robust or not.
`eff`	A `double` that specifies the amount of efficiency required by the robust estimator.
`inference`	A `bool` that indicates whether inference (e.g. GoF) should be run.
`fullV`	A `bool` that indicates whether the matrix has been fully bootstrapped.
`bs_gof`	A `bool` indicating whether the GoF should be bootstrapped or done asymptotically.
`bs_gof_p_ci`	A `bool` indicating whether a bootstrapped p-value should be generated during the bootstrapped GoF
`bs_ci`	A `bool` that indicates whether a bootstrapped CI should be obtained or to use analytical derivatives.
`B`	A `int` that indicates how many iterations should take place.