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Prepare data for single RoC estimation

Source: R/prepare_data.R
prepare_data.Rd

Create a single list with all information needed to estimate RoC. This list can then be evaluated in parallel across randomisation runs.

Usage

prepare_data(
  data_source_prep,
  working_units = c("levels", "bins", "MW"),
  bin_size = 500,
  number_of_shifts = 5,
  rand = NULL
)

Arguments

data_source_prep

List with community and age

working_units

character. Strategy used to define Working Units between which dissimilarity is calculated.

  • "levels" - each stratigraphical level is its own WU.

  • "bins" - one representative level is selected from each time bin of width bin_size.

  • "MW" - moving-window binning: selective binning is repeated number_of_shifts times, shifting the window by bin_size / number_of_shifts years each time. All results are retained and summarised together.

bin_size

numeric. Width of each time bin in years. Used when working_units is "bins" or "MW".

number_of_shifts

numeric. Number of window shifts in moving-window binning (working_units = "MW").

rand

numeric. Number of randomisation runs. Set to NULL (default) to skip randomisation and use a single deterministic run.

Value

A list with preprocessed data and bins elements.