Update Wrapper for the GMWM Estimator

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Description

This function uses information obtained previously (e.g. WV covariance matrix) to re-estimate a different model parameterization

Usage

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gmwm_update_cpp(theta, desc, objdesc, model_type, N, expect_diff, ranged, orgV,
  scales, wv, starting, compute_v, K, H, G, robust, eff)

Arguments

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

scales

A vec that contains the scales or taus (2^(1:J))

starting

A bool that indicates whether we guessed starting (T) or the user supplied estimates (F).

wv_empir

A vec that contains the empirical wavelet variance

omega

A mat that represents the covariance matrix.

Value

A field<mat> that contains the parameter estimates from GMWM estimator.

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

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