CI_Method: Conservativeness Index (CI)
In eead-csic-eesa/fingerPro: Sediment Source Fingerprinting
CI_Method R Documentation
Conservativeness Index (CI)
Description
The function quantify the predictions of each individual tracer in your dataset and calculate the CI value of each tracer.
Usage
CI_Method(data, points = 2000, Means = F, seed = 123456L)
Arguments
data
Data frame containing sediment source and mixtures
points
Number of solutions per tracer
Means
Boolean to switch when using mean and sd data
seed
Seed for the random number generator
Value
List of data frames containing the selected number of possible prediction for each tracer. The last lists correspond to the dataset and the CI index.
eead-csic-eesa/fingerPro documentation built on June 28, 2023, 1:39 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| CI_Method | R Documentation |
Conservativeness Index (CI)
Description
The function quantify the predictions of each individual tracer in your dataset and calculate the CI value of each tracer.
Usage
CI_Method(data, points = 2000, Means = F, seed = 123456L)
Arguments
data |
Data frame containing sediment source and mixtures |
points |
Number of solutions per tracer |
Means |
Boolean to switch when using mean and sd data |
seed |
Seed for the random number generator |
Value
List of data frames containing the selected number of possible prediction for each tracer. The last lists correspond to the dataset and the CI index.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.