gen_lts

An <code>interger</code> containing the amount of observations for the time series.

A <code>vec</code> containing the parameters to use to generate the model.

theta

A <code>vector<string></string></code> containing the different model types (AR1, WN, etc..).

desc

A <code>field<vec></vec></code> containing the different model objects e.g. AR1 = c(1,1)

objdesc


Create a latent time series based on a supplied time series model.


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.

gen_lts: Generate Latent Time Series based on Model (Internal)

Description

Usage

Arguments

Value

Examples