update.gmwm: Update (Robust) GMWM object for IMU or SSM

In simts: Time Series Analysis Tools

Update (Robust) GMWM object for IMU or SSM

Description

Provides a way to estimate different models over the previously estimated wavelet variance values and covariance matrix.

Usage

## S3 method for class 'gmwm'
update(object, model, ...)

Arguments

object	A gmwm object.
model	A ts.model object containing one of the allowed models
...	Additional parameters (not used)

Value

A gmwm object with the structure:

• estimateEstimated Parameters Values from the GMWM Procedure

• init.guessInitial Starting Values given to the Optimization Algorithm

• wv.empirThe data's empirical wavelet variance

• ci_lowLower Confidence Interval

• ci_highUpper Confidence Interval

• orgVOriginal V matrix

• VUpdated V matrix (if bootstrapped)

• omegaThe V matrix inversed

• obj.funValue of the objective function at Estimated Parameter Values

• theoSummed Theoretical Wavelet Variance

• decomp.theoDecomposed Theoretical Wavelet Variance by Process

• scalesScales of the GMWM Object

• robustIndicates if parameter estimation was done under robust or classical

• effLevel of efficiency of robust estimation

• model.typeModels being guessed

• compute.vType of V matrix computation

• augmentedIndicates moments have been augmented

• alphaAlpha level used to generate confidence intervals

• expect.diffMean of the First Difference of the Signal

• NLength of the Signal

• GNumber of Guesses Performed

• HNumber of Bootstrap replications

• KNumber of V matrix bootstraps

• modelts.model supplied to gmwm

• model.hatA new value of ts.model object supplied to gmwm

• startingIndicates whether the procedure used the initial guessing approach

• seedRandomization seed used to generate the guessing values

• freqFrequency of data

simts documentation built on Aug. 31, 2023, 5:07 p.m.