Attaches a bootstrap confidence interval (and standard error) to the
Lomb-Scargle period estimate from circadian.period. Because
activity is strongly autocorrelated, an i.i.d. resample would destroy the
rhythm and give an invalid (too-narrow) interval, so a circular
moving-block bootstrap of the cosinor residuals is used: the rhythm fitted at
the point estimate is held fixed while blocks of residuals are resampled, the
periodogram peak is re-located on each replicate (with sub-grid parabolic
refinement), and the interval is taken from the quantiles of the replicate
periods.
Usage
period.ci(
counts,
timestamps,
from = 18,
to = 30,
ofac = 4,
n_boot = 200,
block_hours = 24,
level = 0.95,
seed = NULL
)Arguments
- counts
Numeric activity vector;
NAare dropped with their times.- timestamps
POSIXct (or numeric-coercible) timestamps, same length.
- from, to
Period search window in hours (default 18, 30).
- ofac
Integer oversampling factor for the period grid (default 4).
- n_boot
Number of bootstrap replicates (default 200).
- block_hours
Moving-block length in hours (default 24).
- level
Confidence level (default 0.95).
- seed
Optional integer seed passed to
set.seedfor reproducible bootstrap draws.
Value
An object of class actiRhythm_period_ci: a list with tau
(the point estimate, hours), ci_lower/ci_upper, se, the
level, the number of valid replicates, and tau_boot (the vector
of bootstrap replicate periods).
References
Kunsch HR (1989). “The jackknife and the bootstrap for general stationary observations.” The Annals of Statistics, 17(3), 1217–1241. doi:10.1214/aos/1176347265 .
Politis DN, Romano JP (1992). “A circular block-resampling procedure for stationary data.” In LePage R, Billard L (eds.), Exploring the Limits of Bootstrap, 263–270. Wiley, New York.
Examples
# \donttest{
t_hours <- seq(0, 5 * 24 - 1/60, by = 1/60)
ts <- as.POSIXct("2024-01-01", tz = "UTC") + t_hours * 3600
counts <- 100 + 80 * cos(2 * pi * (t_hours - 8) / 24) + rnorm(length(t_hours), 0, 20)
period.ci(counts, ts, n_boot = 50, seed = 1)
#> Circadian Period with Bootstrap Confidence Interval
#>
#> tau: 24.088 h
#> 95% CI: [23.975, 24.051] h
#> SE: 0.020 h
#> Method: circular block residual bootstrap (50/50 valid reps)
# }