| Title: | Detect Sensitive Points in the Tail |
| Version: | 1.0.0 |
| Description: | The goal of 'TailID' is to detect sensitive points in the tail of a dataset using techniques from Extreme Value Theory (EVT). It utilizes the Generalized Pareto Distribution (GPD) for assessing tail behavior and detecting inconsistent points with the Identical Distribution hypothesis of the tail. For more details see Manau (2025)<doi:10.4230/LIPIcs.ECRTS.2025.20>. |
| License: | GPL (≥ 3) |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.3 |
| Imports: | ggplot2, grDevices, ismev, scales |
| Language: | en-US |
| NeedsCompilation: | no |
| Packaged: | 2025-09-09 10:43:25 UTC; bmanau |
| Author: | Blau Manau  [aut,
cre] |
| Maintainer: | Blau Manau <blau.manau@bsc.es> |
| Repository: | CRAN |
| Date/Publication: | 2025-09-14 16:00:02 UTC |
Computes a Confidence Interval for a GPD shape
Description
This function computes a confidence interval for a GPD shape.
Usage
CI_shapeGPD(sample, threshold, parameter, conf_level)
Arguments
sample |
A numeric vector. |
threshold |
A number between 0 and 1 indicating the threshold of extreme values to consider. |
parameter |
A number indicating the shape value. |
conf_level |
A number between 0 and 1 indicating the confidence level for the detection. |
Value
A Confidence Interval vector.
Examples
CI_shapeGPD(rnorm(1000), 0.8, 1, 0.95)
CI_shapeGPD(c(rnorm(10^3,10,1),rnorm(10,20,3)), 0.8, 12, 0.9999)
Detects the sensitive points in the Tail
Description
This function returns the points of the tail that are inconsistent with the ID hypothesis.
Usage
TailID(sample, pm_max, pm_min, pc_max, pc_min, conf_level)
Arguments
sample |
A numeric vector. |
pm_max |
A number between 0 and 1 indicating the threshold of maximum extreme values to consider. |
pm_min |
A number between 0 and 1 indicating the threshold of minimum extreme values to consider. |
pc_max |
A number between pm_max and 1 indicating the threshold of maximum sensitive points to consider. |
pc_min |
A number between pm_min and 1 indicating the threshold of minimum sensitive points to consider. |
conf_level |
A number between 0 and 1 indicating the confidence level for the detection. |
Value
A vector of indices corresponding to the detected sensitive points.
Examples
TailID(rnorm(1000), 0.8, 0.8, 0.99, 0.99, 0.95)
TailID(c(rnorm(10^3,10,1),rnorm(10,20,3)), 0.8, 0.8, 0.9, 0.9, 0.9999)
Selects the candidates of the tail
Description
This function selects the candidates of the tail that can be inconsistent to the ID hypothesis
Usage
candidate_selection(sample, pc_max, pc_min)
Arguments
sample |
A numeric vector. |
pc_max |
A number between pm_max and 1 indicating the threshold of maximum sensitive points to consider. |
pc_min |
A number between pm_min and 1 indicating the threshold of minimum sensitive points to consider. |
Value
A vector of indices corresponding to the detected sensitive points.
Examples
candidate_selection(rnorm(1000), 0.99, 0.99)
candidate_selection(c(rnorm(10^3,10,1),rnorm(10,20,3)), 0.9, 0.9)
Saves the plots corresponding to the TailID detection
Description
This function saves the plots corresponding to the TailID detection, which includes: targeted candidates plot, shape variation plot, and inconsistent detected points.
Usage
plot_TailID(output_dir, sample, pm_max, pm_min, pc_max, pc_min, conf_level)
Arguments
output_dir |
Path to save the plots. |
sample |
A numeric vector. |
pm_max |
A number between 0 and 1 indicating the threshold of maximum extreme values to consider. |
pm_min |
A number between 0 and 1 indicating the threshold of minimum extreme values to consider. |
pc_max |
A number between pm_max and 1 indicating the threshold of maximum sensitive points to consider. |
pc_min |
A number between pm_min and 1 indicating the threshold of minimum sensitive points to consider. |
conf_level |
A number between 0 and 1 indicating the confidence level for the detection. |
Value
A vector of indices corresponding to the detected sensitive points.
Examples
output_dir <- file.path(tempdir(), "output")
if (dir.exists(output_dir) || dir.create(output_dir, recursive = TRUE)) {
plot_TailID(output_dir, rnorm(1000), 0.85, 0.85, 0.999, 0.999, 0.95)
}
if (dir.exists(output_dir) || dir.create(output_dir, recursive = TRUE)) {
plot_TailID(output_dir, c(rnorm(10^3, 10, 1), rnorm(10, 20, 3)), 0.85, 0.85, 0.99, 0.99, 0.99999)
}
Evaluation of the shape parameter to return inconsistent points and shape parameters computed and its confidence intervals
Description
This function detects the points of the tail that are inconsistent with the ID hypothesis by evaluation the shape variation of the GPD, and also returns the shape parameters computed and its confidence intervals
Usage
shape_evaluation(sample, candidates, pm_max, pm_min, conf_level)
Arguments
sample |
A numeric vector. |
candidates |
A list of indices of the sample. |
pm_max |
A number between 0 and 1 indicating the threshold of maximum extreme values to consider. |
pm_min |
A number between 0 and 1 indicating the threshold of maximum extreme values to consider. |
conf_level |
A number between 0 and 1 indicating the confidence level for the detection. |
Value
A vector of indices corresponding to the detected sensitive points.
Examples
shape_evaluation(rnorm(1000),candidate_selection(rnorm(1000), 0.99, 0.99),
0.8, 0.8, 0.95)
shape_evaluation(c(rnorm(10^3,10,1),rnorm(10,20,3)),
candidate_selection(c(rnorm(10^3,10,1),rnorm(10,20,3)), 0.9, 0.9),
0.8, 0.8, 0.9999)