CI: Compute Conservativeness Index (CI) for individual tracers
In fingerPro: A Comprehensive Package for Sediment Source Unmixing
CI R Documentation
Compute Conservativeness Index (CI) for individual tracers
Description
This function calculates the Conservativeness Index (CI) for each tracer based on the results of an individual tracer analysis.
The CI index was adapted from its original definition to better describe the conservativeness of tracers in a high-dimensional space of multiple sources. The predicted source contributions from each tracer were first calculated and characterized by their centroid. Then, the CI index was calculated as the percentage of solutions with conservative apportionments (0 <= wi <= 1) relative to the centroid position. This new definition of the CI does not penalize tracers with dominant apportionments from one source and distributions close to a vertex of the physical space, unlike the previous definition.
Usage
CI(ita)
Arguments
ita
A list of data frames, where each data frame contains the predicted apportionments for a specific tracer, as obtained from the 'individual_tracer_analysis' function.
Value
A data frame containing the CI value for each tracer.
References
Lizaga, I., Latorre, B., Bodé, S., Gaspar, L., Boeckx, P., & Navas, A. (2024). Combining isotopic and elemental tracers for enhanced sediment source partitioning in complex catchments. *Journal of Hydrology*, 631, 130768. https://doi.org/10.1016/j.jhydrol.2024.130768
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
fingerPro documentation built on Aug. 27, 2025, 5:11 p.m.
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| CI | R Documentation |
Compute Conservativeness Index (CI) for individual tracers
Description
This function calculates the Conservativeness Index (CI) for each tracer based on the results of an individual tracer analysis.
The CI index was adapted from its original definition to better describe the conservativeness of tracers in a high-dimensional space of multiple sources. The predicted source contributions from each tracer were first calculated and characterized by their centroid. Then, the CI index was calculated as the percentage of solutions with conservative apportionments (0 <= wi <= 1) relative to the centroid position. This new definition of the CI does not penalize tracers with dominant apportionments from one source and distributions close to a vertex of the physical space, unlike the previous definition.
Usage
CI(ita)
Arguments
ita |
A list of data frames, where each data frame contains the predicted apportionments for a specific tracer, as obtained from the 'individual_tracer_analysis' function. |
Value
A data frame containing the CI value for each tracer.
References
Lizaga, I., Latorre, B., Bodé, S., Gaspar, L., Boeckx, P., & Navas, A. (2024). Combining isotopic and elemental tracers for enhanced sediment source partitioning in complex catchments. *Journal of Hydrology*, 631, 130768. https://doi.org/10.1016/j.jhydrol.2024.130768
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
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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