pairingits {iAR}

Pairing two irregularly observed time series

Description

Pairing the observational times of two irregularly observed time series

Usage

pairingits(lc1, lc2, tol = 0.1)

Arguments

lc1

data frame with three columns corresponding to the first irregularly observed time series. The columns must be ordered as follow: First the observational times, second the measures of each time, and third the measurement errors.

lc2

data frame with three columns corresponding to the second irregularly observed time series. The columns must be ordered as follow: First the observational times, second the measures of each time, and third the measurement errors.

tol

tolerance parameter. Minimum time gap to consider that two observations have measured at different times.

Value

A list with the following components:

• n Number of observations paired by their observational times.

• parData Frame with the paired datasets.

References

Elorrieta F, Eyheramendy S, Palma W, Ojeda C (2021). “A novel bivariate autoregressive model for predicting and forecasting irregularly observed time series.” Monthly Notices of the Royal Astronomical Society, 505(1), 1105–1116. ISSN 0035-8711, doi: 10.1093/mnras/stab1216, https://academic.oup.com/mnras/article-pdf/505/1/1105/38391762/stab1216.pdf.

See Also

cvnovag, cvnovar, BIARkalman

Examples

data(cvnovag)
data(cvnovar)
pargr=pairingits(cvnovag,cvnovar,tol=0.1)