gmwm_param_bootstrapper

A <code>vector</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> that contains an object description (e.g. values) of the model.

objdesc


Using the bootstrap approach, we simulate a model based on user supplied parameters, obtain the wavelet variance, and then V.


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_param_bootstrapper: Bootstrap for Estimating Both Theta and Theta SD

Description

Usage

Arguments

Value

Details

Examples