CTS_3_sources: CTS Engine for 3 Sources

View source: R/CTS_3_sources.R

CTS_3_sourcesR Documentation

CTS Engine for 3 Sources

Description

Solves determined systems for 2 tracers and 3 sources to assess solution dispersion and discriminant capacity.

Usage

CTS_3_sources(source, mixture, iter = 1000, seed = 123456, verbose = TRUE)

pairs(source, mixture, iter = 1000, seed = 123456, verbose = TRUE)

CTS_seeds_pairs(source, mixture, iter = 1000, seed = 123456, verbose = TRUE)

Arguments

source

Data frame of sediment sources containing 3 source rows, mean values, standard deviations, and sample size ('n').

mixture

Data frame of mixture samples.

iter

Number of Monte Carlo iterations. Default is 1000.

seed

Integer seed for reproducibility. Default is 123456.

verbose

Logical. Whether to show a progress bar in the console. Default is TRUE.

Value

A data.frame ordered by max_dw (lowest dispersion first) containing:

id

Pair of tracer names used for the system.

w1, w2, w3

Calculated proportion contributions for Sources 1, 2, and 3.

dw1, dw2, dw3

Dispersion uncertainties for Sources 1, 2, and 3 (half 84% - 16% quantile range).

cons

Proportion of Monte Carlo iterations yielding physically valid proportions between 0 and 1.

max_dw

Maximum dispersion uncertainty across all three sources.

Examples

# Prepare small dummy datasets for 3 sources and 2 tracers
src <- data.frame(
  ID = c("Src1", "Src2", "Src3"),
  Tracer1 = c(10.5, 20.2, 5.0),
  Tracer2 = c(2.1, 8.5, 12.3),
  Tracer1_SD = c(1.1, 1.8, 0.5),
  Tracer2_SD = c(0.3, 0.9, 1.1),
  n = c(10, 10, 10)
)
mix <- data.frame(ID = "Mix1", Tracer1 = 12.0, Tracer2 = 6.0)

# Run engine
result <- CTS_3_sources(source = src, mixture = mix, iter = 100, verbose = FALSE)
head(result)


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