pairingits: Pairing two irregularly observed time series

In iAR: Irregularly Observed Autoregressive Models

Pairing two irregularly observed time series

Description

This method pairs the observational times of two irregularly observed time series.

Usage

pairingits(x, ...)

Arguments

x	An object of class 'utilities'.
...	Additional arguments for pairing time series: lc1 A data frame with three columns corresponding to the first irregularly observed time series. lc2 A data frame with three columns corresponding to the second irregularly observed time series. tol A numeric value indicating the tolerance parameter.

Details

The method checks the observational times in both input time series and pairs the measurements if they fall within the specified tolerance ('tol'). If a measurement in one series cannot be paired, it is filled with 'NA' values for the corresponding columns of the other series.

Value

An object of class 'utilities' with two slots:

series	A matrix containing the paired time series, where unmatched measurements are filled with 'NA'.
series_esd	A matrix containing the paired error standard deviations of the time series, where unmatched measurements are filled with 'NA'.
times	A numeric vector with the paired observational times.

References

\insertRef

Elorrieta_2021iAR

Examples

data(cvnovag)
data(cvnovar)
datag=cvnovag
datar=cvnovar
o1=iAR::utilities()
o1<-pairingits(o1, datag,datar,tol=0.1)
pargr1=na.omit(o1@paired)
st=apply(pargr1[,c(1,4)],1,mean)
model_BiAR <- BiAR(times = st,series=pargr1[,c(2,5)],series_esd=pargr1[,c(3,6)])
model_BiAR <- kalman(model_BiAR)

iAR documentation built on April 4, 2025, 2:21 a.m.