harmonicfit: Harmonic Fit to Time Series

In iAR: Irregularly Observed Autoregressive Models

Harmonic Fit to Time Series

Description

This function fit an k-harmonic function to time series data.

Usage

harmonicfit(x, ...)

Arguments

x

An object of class 'utilities'.

...

Additional arguments for pairing time series: data A data frame with three columns corresponding to the time, values, and standard errors of the irregularly observed time series. f1 frequency (1 / period) of the time series. nham Number of harmonic components in the model. weighted logical; if true, a weighted least squares (WLS) estimation is performed using weights based on the standard deviations of the errors. Default is 'FALSE'. remove_trend logical; if true, the linear trend of time series will be removed before the the harmonic model is fitted.

Details

The function fits a harmonic regression model with 'nham' components to the input time series, optionally removing a linear trend and allowing for weighted estimation when standard errors are available.

Value

An object of class 'utilities' with the slots:

fitted_values	Fitted values from the harmonic model.
residuals	Residuals from the harmonic model.
coef	Estimated coefficients of the harmonic model.
summary	A summary object containing detailed model information.

References

\insertRef

Elorrieta_2021iAR

Examples

data(clcep)
f1=0.060033386
o1=iAR::utilities()
o1<-phase(o1,data=clcep,f1=f1)
#results$R2
#results$MSE
#results=harmonicfit(file=clcep[,1:2],f1=f1,nham=3)
#results$R2
#results$MSE
#results=harmonicfit(file=clcep[,1:2],f1=f1,weights=clcep[,3])
#results$R2
#results$MSE

iAR documentation built on Nov. 5, 2025, 6:19 p.m.