model_score

A <code>mat</code> that contains the first derivatives of the processes

A <code>mat</code> that contains the omega used when calculating the GMWM

omega

A <code>mat</code> that contains the covariance matrix

v_hat

A <code>mat</code> that contains the second derivative of each process

At_j

A <code>vec</code> that is the difference of the WV empirical and WV theoretical

diff


Calculates the modeling score of a GMWM


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.

model_score: Model Score

Description

Usage

Arguments

Value

Details