Pools single-subject cosinor fits into a group-mean rhythm with confidence
intervals, following Bingham et al. (1982). Fits each subject's averaged
24-hour profile with the same weighted-least-squares engine as
cosinor.analysis, averages the linearized cos/sin coefficients
across subjects, and returns the group MESOR, amplitude, and acrophase with
Bingham confidence intervals.
Usage
population.cosinor(
activity,
timestamps,
subject,
group = NULL,
period = 24,
level = 0.95,
min_valid_hours = 12
)Arguments
- activity
Numeric activity vector with all subjects stacked together.
- timestamps
POSIXct timestamps, one per value.
- subject
Subject identifier, one per value.
- group
Optional group identifier, one per value; when supplied a population cosinor is returned for each group.
- period
Rhythm period in hours (default 24).
- level
Confidence level (default 0.95).
- min_valid_hours
Minimum profile hours for a subject to be included (default 12).
Value
An object of class actiRhythm_population_cosinor (group MESOR,
amplitude, acrophase with Bingham CIs and a conf_interval_valid
flag), or a named list of them (class
actiRhythm_population_cosinor_list) when group is supplied.
References
Bingham C, Arbogast B, Cornelissen Guillaume G, Lee JK, Halberg F (1982). “Inferential statistical methods for estimating and comparing cosinor parameters.” Chronobiologia, 9(4), 397–439.
Examples
set.seed(1)
hrs <- 0:23
act <- ts <- subj <- NULL
for (i in 1:6) {
y <- 100 + 40 * cos(2 * pi * (hrs - (8 + i / 3)) / 24) + rnorm(24, 0, 4)
act <- c(act, y); subj <- c(subj, rep(paste0("S", i), 24))
ts <- c(ts, as.POSIXct("2024-01-01", tz = "UTC") + hrs * 3600)
}
population.cosinor(act, as.POSIXct(ts, tz = "UTC", origin = "1970-01-01"), subj)
#> Population-Mean Cosinor (Bingham)
#>
#> Subjects: 6
#> Period: 24 h
#> MESOR: 100.17 [99.32, 101.01]
#> Amplitude: 39.68 [38.54, 40.81]
#> Acrophase: 9.71 h [9.05, 10.34]