gmwm_master_cpp: Master Wrapper for the GMWM Estimator
In SMAC-Group/gmwm: Generalized Method of Wavelet Moments

Description Usage Arguments Value Author(s) References

This function generates WV, GMWM Estimator, and an initial test estimate.

1 2	gmwm_master_cpp(data, theta, desc, objdesc, model_type, starting, alpha, compute_v, K, H, G, robust, eff)

`data`	A `vec` containing the data.
`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
`starting`	A `bool` that indicates whether the supplied values are guessed (T) or are user-based (F).
`alpha`	A `double` that handles the alpha level of the confidence interval (1-alpha)*100
`compute_v`	A `string` that describes what kind of covariance matrix should be computed.
`K`	An `int` that controls how many times theta is updated.
`H`	An `int` that controls how many bootstrap replications are done.
`G`	An `int` that controls how many guesses at different parameters are made.
`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.

A field<mat> that contains a list of ever-changing estimates...

JJB

Wavelet variance based estimation for composite stochastic processes, S. Guerrier and Robust Inference for Time Series Models: a Wavelet-Based Framework, S. Guerrier

SMAC-Group/gmwm documentation built on Sept. 11, 2021, 10:06 a.m.