optimism_bootstrapper

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

theta

A <code>vector&lt;string&gt;</code> indicating the models that should be considered.

desc

A <code>field&lt;vec&gt;</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

A system contains easy-to-use tools as a support for time series analysis courses. In particular, it incorporates a technique called Generalized Method of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust parameter estimation of time series models which is described, for example, in Guerrier et al. (2013) <doi: 10.1080/01621459.2013.799920>. More details can also be found in the paper linked to via the URL below.

St<c3><a9>phane Guerrier

simts

Time Series Analysis Tools

James Balamuta

Roberto Molinari

Justin Lee

Yuming Zhang

Wenchao Yang

Nathanael Claussen

Yunxiang Zhang

Christian Gunning

Romain Francois

Ross Ihaka

R Core Team 

optimism_bootstrapper function

Bootstrap for Optimism — optimism_bootstrapper

Bootstrap for Optimism

optimism_bootstrapper: Bootstrap for Optimism

Description

Usage

Arguments

Value

Details