Adaptive COCO — coco_adaptive • WaverideR

Modern Acycle adaptive COCO: nine-term orbital target synthesised on the finite record at every tested rate, amplitudes fitted to the spectrum, AR(1) Monte Carlo null with global (max-over-rate) and local p-values. Translated from Acycle corrcoefslices_rankNew.m (Mingsong Li).

Usage

coco_adaptive(
  data,
  orbit9 = orbit9_default(),
  sr = seq(0.5, 20, by = 0.1),
  pad = 5000,
  red = 1,
  nsim = 1000,
  slices = 1,
  method = c("Pearson", "Spearman"),
  max_frequency = NULL,
  amplitude_mode = c("four-group-area", "per-orbit", "fixed"),
  target_model = c("coherent-nine", "phase-averaged"),
  seed = 1,
  batch = NULL,
  verbose = TRUE
)

Arguments

data: Record to analyse (matrix or data frame, two columns): depth in metres in column 1 and the proxy in column 2. Non-finite rows are dropped, duplicated depths averaged, and unevenly spaced data are linearly interpolated to the median sample spacing (see coco_prepare_regular_data). Required, no default.
orbit9: The nine astronomical target periods in kyr (numeric vector of nine distinct values: long eccentricity, four short eccentricity terms, obliquity, three precession terms), e.g. from orbit9_at_age or calculate_orbit9 for the age of the record. The default uses the present-day periods (405.7, 130.7, 123.9, 98.9, 94.9, 41.0, 23.7, 22.4 and 19.0 kyr). Default=orbit9_default().
sr: Sedimentation rates to test, in cm/kyr (numeric vector, > 0); the correlation is computed for every value. Default=seq(0.5, 20, by = 0.1).
pad: Length (number of points) to which every slice is zero-padded for the periodogram (integer, at least the number of samples in the longest slice); a larger value gives a finer frequency grid. Default=5000.
red: Background (red-noise) removal applied to every spectrum before the correlation (integer): 0 no removal, 1 classical AR(1) background subtracted, 2 robust AR(1) background (median-smoothed spectrum, Mann and Lees 1996 style), 3 smoothed-window-average (SWA) background (needs at least 33 spectral bins). Negative power after subtraction is set to zero. Default=1.
nsim: Number of AR(1) Monte Carlo simulations used for the global and local p-values (integer, >= 0); 0 skips the simulations, so no p-values or pCOCO are returned. Default=1000.
slices: Number of equal-depth slices into which the record is cut; each slice is standardised and detrended and their spectra are averaged (integer, >= 1; every slice needs at least 4 points). Default=1.
method: Correlation coefficient between the data spectrum and the target spectrum (character): "Pearson" or "Spearman". Default=c("Pearson", "Spearman"), i.e. "Pearson".
max_frequency: Highest frequency of the target spectrum that enters the correlation, in cycles/kyr (numeric, must be at least the highest orbital frequency max(1/orbit9)); NULL uses 1.2 * max(1/orbit9). Default=NULL.
amplitude_mode: How the amplitudes of the nine target sinusoids are set (character): "four-group-area" fits one amplitude per group (long eccentricity, short eccentricity, obliquity, precession) to the band areas of the data spectrum (Acycle default; needs target_model="coherent-nine"), "per-orbit" fits each of the nine amplitudes to the spectral peak at its frequency, "fixed" uses fixed weights (1.0 eccentricity, 0.8 obliquity, 0.6 precession; see coco_fixed_target_weights). Default=c("four-group-area", "per-orbit", "fixed"), i.e. "four-group-area".
target_model: How the target spectrum is synthesised on the finite record (character): "coherent-nine" (the spectrum of the sum of the nine sinusoids, including their interference) or "phase-averaged" (the sum of the individual spectra, averaged over sine and cosine phase). Default=c("coherent-nine", "phase-averaged"), i.e. "coherent-nine".
seed: Seed of the random number generator (integer), so that the Monte Carlo results can be reproduced; NULL leaves the current random state unchanged. Default=1.
batch: Number of Monte Carlo simulations processed together in one batch (integer, >= 1); larger batches are faster but use more memory. NULL chooses it from pad (about 4 million spectral values per batch). Default=NULL.
verbose: Print messages about the preprocessing and the progress of the Monte Carlo simulations (logical, TRUE or FALSE). Default=TRUE.

Value

list with `result` data.frame: sr, rho, p_param, p_global, p_local, norbit, pcoco