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gmwm (version 2.0.0)

gmwm_master_cpp: Master Wrapper for the GMWM Estimator

Description

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

Usage

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

Arguments

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 indicating the models that should be considered.
objdesc
A field 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.

Value

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

References

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