Computing phased time series

This function computes a time series folded on its period.

Usage

phase(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.

twop

logical; if TRUE, the phased series will be duplicated over two cycles (0–2).

Value

An object of class `utilities` with the slots:

series_phased

A numeric vector containing the time series values ordered by phase.

series_esd_phased

A numeric vector containing the error standard deviations of the time series ordered by phase.

times_phased

A numeric vector of phased times (values between 0 and 1, or 0 and 2 if 'two.cycles = TRUE').

Details

The phase \(\phi\) of an observation is computed as $$\phi = \frac{t - t_0}{p} - \mathrm{E}(t),$$ where \(t_0\) is the reference time (by default the first observation), \(p = 1/f_1\) is the period, and \(\mathrm{E}(t)\) is the integer part of \((t - t_0)/p\).

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.

Examples

data(clcep)
f1=0.060033386
o1=iAR::utilities()
o1<-phase(o1,data=clcep,f1=f1,twop=TRUE)
plot(o1@times_phased,o1@series_phased,pch=20)