gmwm_master_cpp: Master Wrapper for the GMWM Estimator

View source: R/RcppExports.R

gmwm_master_cppR Documentation

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<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.

Value

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

Author(s)

JJB

References

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/simts documentation built on Sept. 4, 2023, 5:25 a.m.