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:

estimate	Estimated Parameters Values from the GMWM Procedure
init.guess	Initial Starting Values given to the Optimization Algorithm
wv.empir	The data's empirical wavelet variance
ci_low	Lower Confidence Interval
ci_high	Upper Confidence Interval
orgV	Original V matrix
V	Updated V matrix (if bootstrapped)
omega	The V matrix inversed
obj.fun	Value of the objective function at Estimated Parameter Values
theo	Summed Theoretical Wavelet Variance
decomp.theo	Decomposed Theoretical Wavelet Variance by Process
scales	Scales of the GMWM Object
robust	Indicates if parameter estimation was done under robust or classical
eff	Level of efficiency of robust estimation
model.type	Models being guessed
compute.v	Type of V matrix computation
augmented	Indicates moments have been augmented
alpha	Alpha level used to generate confidence intervals
expect.diff	Mean of the First Difference of the Signal
N	Length of the Signal
G	Number of Guesses Performed
H	Number of Bootstrap replications
K	Number of V matrix bootstraps
model	ts.model supplied to gmwm
model.hat	A new value of ts.model object supplied to gmwm
starting	Indicates whether the procedure used the initial guessing approach
seed	Randomization seed used to generate the guessing values
freq	Frequency of data

simts documentation built on Nov. 5, 2025, 7:17 p.m.