scanstatistics: Space-Time Anomaly Detection using Scan Statistics

Detection of anomalous space-time clusters using the scan statistics methodology. Focuses on prospective surveillance of data streams, scanning for clusters with ongoing anomalies. Hypothesis testing is made possible by Monte Carlo simulation. Allévius (2018) <doi:10.21105/joss.00515>.

Version: 1.1.1
Depends: R (≥ 3.4)
Imports: dplyr, ismev, magrittr, plyr, Rcpp, stats, sets, tibble, tidyr
LinkingTo: Rcpp, RcppArmadillo
Suggests: purrr, doParallel, foreach, ggplot2, knitr, MASS, pscl, reshape2, rmarkdown, sp, testthat, gamlss.dist
Published: 2023-01-26
Author: Benjamin Allévius [aut], Paul Romer Present [ctb, cre]
Maintainer: Paul Romer Present <paul.romerpresent at fastmail.fm>
BugReports: https://github.com/promerpr/scanstatistics/issues
License: GPL (≥ 3)
URL: https://github.com/promerpr/scanstatistics
NeedsCompilation: yes
SystemRequirements: C++11
Citation: scanstatistics citation info
Materials: README NEWS
CRAN checks: scanstatistics results

Documentation:

Reference manual: scanstatistics.pdf
Vignettes: Introduction to scanstatistics

Downloads:

Package source: scanstatistics_1.1.1.tar.gz
Windows binaries: r-devel: scanstatistics_1.1.1.zip, r-release: scanstatistics_1.1.1.zip, r-oldrel: scanstatistics_1.1.1.zip
macOS binaries: r-release (arm64): scanstatistics_1.1.1.tgz, r-oldrel (arm64): scanstatistics_1.1.1.tgz, r-release (x86_64): scanstatistics_1.1.1.tgz
Old sources: scanstatistics archive

Reverse dependencies:

Reverse suggests: ssrn

Linking:

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