create_wvar

A <code>matrix</code> with dimensions N x 3, that contains the wavelet variance, low ci, hi ci.

A <code>string</code> that indicates whether to use the "dwt" or "modwt" decomposition

decomp

A <code>boolean</code> that triggers the use of the robust estimate.

robust

A <code>double</code> that indicates the efficiency as it relates to an MLE.

A <code>double</code> that indicates the $(1-p)*alpha$ confidence level

alpha

A <code>vec</code> that contains the amount of decomposition done at each level.

scales

A <code>string</code> that contains the unit expression of the frequency.

unit

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.

create_wvar: Create a Wvar object

Description

Usage

Arguments

Value