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stray
View on CRAN: Click
here
Download and install stray package within the R console
Install from CRAN:
install.packages("stray")
Install from Github:
library("remotes")
install_github("cran/stray")
Install by package version:
library("remotes")
install_version("stray", "0.1.1")
Attach the package and use:
library("stray")
Maintained by
Priyanga Dilini Talagala
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All associated links for this package
First Published: 2019-12-17
Latest Update: 2020-06-29
Description:
This is a modification of 'HDoutliers' package. The 'HDoutliers' algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation. However, it suffers from some limitations that significantly hinder its performance level, under certain circumstances. This package implements the algorithm proposed in Talagala, Hyndman and Smith-Miles (2019) <doi:10.48550/arXiv.1908.04000>for detecting anomalies in high-dimensional data that addresses these limitations of 'HDoutliers' algorithm. We define an anomaly as an observation that deviates markedly from the majority with a large distance gap. An approach based on extreme value theory is used for the anomalous threshold calculation.
How to cite:
Priyanga Dilini Talagala (2019). stray: Anomaly Detection in High Dimensional and Temporal Data. R package version 0.1.1, https://cran.r-project.org/web/packages/stray. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2019-12-17 12:50)
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Complete documentation for stray
Functions, R codes and Examples using
the stray R package
Some associated functions: data_a . data_b . data_c . data_d . data_e . data_f . display_HDoutliers . find_HDoutliers . find_threshold . ped_data . stray . use_KNN . wheel1 .
Some associated R codes: data.R . display_HDoutliers.R . find_HDoutliers.R . find_threshold.R . stray.R . Full stray package functions and examples
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