Evolutionary COCO (Li et al. 2018) — ecoco

COCO in a sliding window (2019 Acycle ecoco.m driver) with best-rate summary and ridge tracking per window.

Usage

ecoco_classic(
  data,
  target,
  orbit = NULL,
  window,
  step = 1,
  sr = seq(0.2, 20, by = 0.2),
  dt = NULL,
  pad = 5000,
  red = 1,
  nsim = 0,
  slices = 1,
  adjust = 0,
  delinear = 1,
  method = c("Pearson", "Spearman"),
  mc = c("first-window", "each-window"),
  seed = NULL,
  track_ridge = TRUE,
  verbose = TRUE
)

Arguments

data: Record to analyse (matrix or data frame; the first two columns are used): depth in metres in column 1 and the proxy in column 2, evenly spaced (it is not interpolated; incomplete rows are dropped and the rows sorted by depth). Required, no default.
target: Astronomical target periodogram (two-column matrix or data frame): frequency in cycles/kyr in column 1 and power in column 2, e.g. the output of coco_target_from_periods or coco_target_from_series; passed to coco_classic for every window. Required, no default.
orbit: Astronomical periods in kyr (numeric vector), used to count how many astronomical parameters contribute at each rate (and, with adjust=1, to define the target bands; then seven periods are needed). NULL uses the periods stored with the target (attribute "orbit"), or else the seven periods of Li et al. (2018) (400, 120.5, 93.1, 38.6, 23.0, 21.8 and 18.5 kyr). Default=NULL.
window: Length of the sliding window, in metres (numeric, > 0; it must contain at least 3 samples and at most the whole record). Required, no default.
step: Step between successive windows, in number of samples (integer, >= 1 and smaller than half the number of samples). Default=1.
sr: Sedimentation rates to test in every window, in cm/kyr (numeric vector, > 0). Default=seq(0.2, 20, by = 0.2).
dt: Sampling interval of data, in metres (numeric, > 0); NULL uses the median spacing of the depth column. It also sets the number of samples per window, trunc(window / dt). Default=NULL.
pad: Length (number of points) to which each window is zero-padded for the periodogram (integer, at least the number of samples per window); a larger value gives a finer frequency grid. Default=5000.
red: Red-noise treatment of the window periodograms, passed to coco_classic (integer): 0 none; 1 the AR(1) background is subtracted (as in Li et al. 2018); 2 the periodogram is divided by the AR(1) background minus 1; 3 a robust AR(1) background (median-smoothed spectrum) is subtracted; a value from 50 to 99 divides by that AR(1) confidence level (in %) minus 1. Negative values are set to zero. Default=1.
nsim: Number of Monte Carlo simulations of the null hypothesis of no astronomical forcing, used for the p-value p_h0 and pCOCO (integer, >= 0; 2000 in Li et al. 2018); 0 skips them and the score becomes norbit * rho. See mc for where the null is simulated. Default=0.
slices: Number of equal-depth slices of each window whose periodograms are averaged (integer, >= 1); 1 uses the whole window. Default=1.
adjust: Adjust the power of the target in four bands (long eccentricity, short eccentricity, obliquity, precession) to the power of the data in those bands at each rate (integer): 0 no, 1 yes (only for a seven-period target). Default=0.
delinear: Remove the mean of each window before the analysis, as in Acycle ecoco.m (numeric): 1 yes, any other value no. Default=1.
method: Correlation coefficient between the data and target spectra (character): "Pearson" (as in Li et al. 2018) or "Spearman". Default=c("Pearson", "Spearman"), i.e. "Pearson".
mc: Where the Monte Carlo null distribution is simulated (character): "first-window" reproduces Acycle 2018-2019, the null is simulated once in the first window and reused for all windows; "each-window" simulates a separate null for every window (slower). Only used when nsim > 0. Default=c("first-window", "each-window"), i.e. "first-window".
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=NULL.
track_ridge: Track a smooth sedimentation-rate ridge through the score map with ecoco_track_ridge (logical, TRUE or FALSE); FALSE returns the best rate per window (ecoco_best_per_window) as track. Default=TRUE.
verbose: Print progress messages for every window (logical, TRUE or FALSE). Default=TRUE.

Value

list of matrices (rows = sr, columns = windows): rho, p_h0, norbit, pcoco, score (= norbit/norb * pcoco) plus `track` (best rate per window)