phase: Computing phased time series

In iAR: Irregularly Observed Autoregressive Models

Computing phased time series

Description

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).

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.

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').

References

\insertRef

Elorrieta_2021iAR

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)

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