gmwm_update_cpp

A <code>vec</code> with dimensions N x 1 that contains user-supplied initial values for parameters

theta

A <code>vector<string></string></code> indicating the models that should be considered.

desc

A <code>field<vec></vec></code> containing a list of parameters (e.g. AR(1) = c(1,1), ARMA(p,q) = c(p,q,1))

objdesc

A <code>string</code> that represents the model transformation

model_type

A <code>vec</code> that contains the scales or taus (2^(1:J))

scales

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

starting

A <code>vec</code> that contains the empirical wavelet variance

wv_empir

A <code>mat</code> that represents the covariance matrix.

omega


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


internal

Generalized Method of Wavelet Moments (GMWM) is an estimation
technique for the parameters of time series models. It uses the wavelet variance
in a moment matching approach that makes it particularly suitable for the
estimation of certain state-space models. Furthermore, there exists a robust
implementation of GMWM, which allows the robust estimation of some state-space
models and ARIMA models. Lastly, the package provides the ability to quickly
generate time series data, perform different wavelet decompositions, and
visualizations.

gmwm_update_cpp: Update Wrapper for the GMWM Estimator

Description

Usage

Arguments

Value

References