CR_Method: Consensus Ranking (CR) method for tracer selection

In OceanTracer: Marine Source Unmixing Toolkit

Consensus Ranking (CR) method for tracer selection

Description

Computes the Consensus Ranking (CR) method, an ensemble technique to identify non-conservative and dissenting tracers. The method combines predictions from single-tracer models and is based on a scoring function derived from a series of random "debates" between tracers, utilizing advanced thresholding logic for extreme datasets.

Usage

CR_Method(
  data,
  debates = 1000,
  completion_quantile = 0.9,
  apportionment_threshold = 0.05,
  seed = 123456,
  verbose = TRUE
)

CR(
  data,
  debates = 1000,
  completion_quantile = 0.9,
  apportionment_threshold = 0.05,
  seed = 123456,
  verbose = TRUE
)

cr_ns(
  data,
  debates = 1000,
  completion_quantile = 0.9,
  apportionment_threshold = 0.05,
  seed = 123456,
  verbose = TRUE
)

Arguments

data	Data frame. Contains source and mixture data in the standard OceanTracer format.
debates	Integer. Target number of random debates per tracer. Default 1000.
completion_quantile	Numeric [0,1]. Quantile threshold for debate completion. For example, 0.5 stops the simulation once half the tracers hit the debates target. Default 0.9.
apportionment_threshold	Numeric. Tolerance boundary for valid debate apportionments (e.g., defining valid as -threshold to 1 + threshold). Default 0.05.
seed	Integer. Random seed for reproducibility. Default 123456.
verbose	Logical. Whether to show a progress bar in the console. Default is TRUE.

Value

A data frame containing the CR score, debates won, and debates lost per tracer.

References

Lizaga, I., Latorre, B., Gaspar, L., & Navas, A. (2020). Consensus ranking as a method to identify non-conservative and dissenting tracers in fingerprinting studies. *Science of The Total Environment*, *720*, 137537. https://doi.org/10.1016/j.scitotenv.2020.137537

OceanTracer documentation built on Oct. 15, 2026, 5:09 p.m.