Package: multiflexscan 0.3.0

Takahiro Otani

multiflexscan: Information Criterion and Scan Statistic Approach for Detecting Multiple Disease Clusters

Detecting multiple disease clusters using the information criterion and scan statistic approach developed by Takahashi and Shimadzu (2020) <doi:10.1186/s12942-020-00228-y>.

Authors:Takahiro Otani [aut, cre], Kunihiko Takahashi [aut]

multiflexscan_0.3.0.tar.gz
multiflexscan_0.3.0.zip(r-4.7-any)multiflexscan_0.3.0.zip(r-4.6-any)multiflexscan_0.3.0.zip(r-4.5-any)
multiflexscan_0.3.0.tgz(r-4.6-any)multiflexscan_0.3.0.tgz(r-4.5-any)
multiflexscan_0.3.0.tar.gz(r-4.7-any)multiflexscan_0.3.0.tar.gz(r-4.6-any)
multiflexscan_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
multiflexscan/json (API)

# Install 'multiflexscan' in R:

install.packages('multiflexscan', repos = c('https://tkhrotn.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tkhrotn/multiflexscan/issues

On CRAN:

4.30 score 301 downloads 9 exports 31 dependencies

Last updated from:4b9bb4b343. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	142
source / vignettes	OK	197
linux-release	OK	141
macos-release	OK	106
macos-oldrel	OK	97
windows-devel	OK	91
windows-release	OK	90
windows-oldrel	OK	88
wasm-release	OK	119

Exports:C_criterion choropleth clusters get_setting model_criteria multiflexscan nclusters pvalue RDC

Dependencies:class classInt cli codetools cpp11 DBI digest doRNG doSNOW e1071 foreach glue igraph iterators KernSmooth lattice lifecycle magrittr Matrix pkgconfig proxy Rcpp rflexscan rlang rngtools s2 sf snow units vctrs wk

A workflow for multiple spatial cluster detection

Prepare aligned spatial inputs | Search and test | Extract and interpret results | Visualize and save

Rendered fromworkflow.Rmdusingknitr::rmarkdown

Last update: 2026-10-05
Started: 2026-10-05

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Detecting multiple spatial disease clusters using the information criterion and scan statistic approach	multiflexscan-package
AIC and BIC for the selected cluster model	AIC.multiflexscan BIC.multiflexscan
Coerce selected clusters to a data frame	as.data.frame.multiflexscan
Draw a choropleth map of multiflexscan clusters	choropleth
Cluster summary table	clusters
Extract selected cluster summaries	coef.multiflexscan
Analysis settings	get_setting
Log-likelihood of the selected cluster model	logLik.multiflexscan
Extract model-selection criteria	C_criterion model_criteria RDC
Detect multiple spatial clusters using the flexible/circular scan statistic	multiflexscan
Number of clusters selected by the information criterion	nclusters
Number of regions in the analysis	nobs.multiflexscan
Plot method for the 'multiflexscan' object. The neighborhood graph is drawn with 'igraph', following 'plot.rflexscan()'.	plot.multiflexscan
Print multiflexscan object	print.multiflexscan
Print summary of multiflexscan results	print.summary.multiflexscan
Overall Monte Carlo p-value	pvalue
Summarizing multiflexscan results	summary.multiflexscan