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(
  file,
  f1,
  nham = 4,
  weights = NULL,
  print = FALSE,
  remove_trend = TRUE
)

Arguments

file	A matrix with two columns. The first column corresponds to the observations times, and the second column corresponds to the measures.
f1	Frequency (1/Period) of the time series
nham	Number of harmonic components in the model
weights	An array with the weights of each observation
print	logical; if true, the summary of the harmonic fitted model will be printed. The default value is false.
remove_trend	logical; if true, the linear trend of time series will be removed before the the harmonic model is fitted.

Value

A list with the following components:

res	Residuals to the harmonic fit of the time series.
t	Observations times.
R2	Adjusted R-Squared.
MSE	Mean Squared Error.
coef	Summary of the coefficients estimated by the harmonic model.

Examples

data(clcep)
f1=0.060033386
#results=harmonicfit(file=clcep[,1:2],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 April 4, 2025, 2:21 a.m.