Package: smerc 1.8.4

smerc: Statistical Methods for Regional Counts

Implements statistical methods for analyzing the counts of areal data, with a focus on the detection of spatial clusters and clustering. The package has a heavy emphasis on spatial scan methods, which were first introduced by Kulldorff and Nagarwalla (1995) <doi:10.1002/sim.4780140809> and Kulldorff (1997) <doi:10.1080/03610929708831995>.

Authors:Joshua French [aut, cre], Mohammad Meysami [ctb]

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smerc.pdf |smerc.html✨
smerc/json (API)
NEWS

# Install 'smerc' in R:
install.packages('smerc', repos = c('https://jfrench.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jfrench/smerc/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • neast - Breast cancer mortality in the Northeastern United States
  • neastw - Binary adjacency matrix for 'neast'
  • nydf - Leukemia data for 281 regions in New York.
  • nypoly - 'SpatialPolygons' object for New York leukemia data.
  • nysf - 'sf' object for New York leukemia data.
  • nysp - 'SpatialPolygonsDataFrame' for New York leukemia data.
  • nyw - Adjacency matrix for New York leukemia data.

On CRAN:

6.33 score 3 stars 3 packages 37 scripts 1.1k downloads 106 exports 3 dependencies

Last updated 30 days agofrom:fb7d17c55c. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-win-x86_64OKNov 23 2024
R-4.5-linux-x86_64OKNov 23 2024
R-4.4-win-x86_64OKNov 23 2024
R-4.4-mac-x86_64OKNov 23 2024
R-4.4-mac-aarch64OKNov 23 2024
R-4.3-win-x86_64OKNov 23 2024
R-4.3-mac-x86_64OKNov 23 2024
R-4.3-mac-aarch64OKNov 23 2024

Exports:all_shape_distsarg_check_dist_ellipsebn.testbn.zonescasewincepp.simcepp.testcepp.weightsclusterscolor.clusterscombine.zonescsg2dc.simdc.testdc.zonesdist.ellipsedistinctdmst.simdmst.testdmst.zonesdweightsedmst.simedmst.testedmst.zoneselbow_pointelliptic.nnelliptic.penaltyelliptic.simelliptic.sim.adjelliptic.testelliptic.zoneseucdistfast.simfast.testfast.zonesflex_testflex_zonesflex.simflex.testflex.zonesgcdistgedistknnlcsg2lgetlgetElementlogical2zonesmc.pvaluemlf.testmlf.zonesmlink.simmlink.testmlink.zonesmorancr.simmorancr.statmorancr.testmst.allmst.seqnclustersnn.cumsumnn2zonesnndistnndupnnpopnoc_ennnoc_nnnozoptimal_ubpopprecog.simprecog.testprep.mstrflex_zonesrflex.midprflex.simrflex.testrflex.zonesscan_statscan.nnscan.simscan.sim.adjscan.statscan.testscan.zonesscsg2seq_scan_simseq_scan_testsgetsgetElementsig_nocsig_prunesmerc_clusterstat_binomstat_binom_adjstat_poissonstat_poisson_adjstat.binomstat.poissonstat.poisson.adjtango.stattango.testtango.weightsuls.simuls.testuls.zonesw2segmentszones.sum

Dependencies:pbapplyRcppRcppProgress

smerc-demo

Joshua P. French

Rendered fromsmerc_demo.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2023-07-07
Started: 2021-01-14

Readme and manuals

Help Manual

Help pageTopics
Besag-Newell Testbn.test
Determine case windows (circles)bn.zones casewin
Perform 'cepp.test' on simulated datacepp.sim
Cluster Evalation Permutation Procedure Testcepp.test
Compute region weights for 'cepp.test'cepp.weights
Extract clustersclusters
Color clusterscolor.clusters
Combine distinct zonescombine.zones
Construct connected subgraphscsg2 lcsg2 scsg2
Perform 'dc.test' on simulated datadc.sim
Double Connection spatial scan testdc.test
Determine zones for the Double Connected scan testdc.zones
Compute minor axis distance of ellipsedist.ellipse
Distinct elements of a listdistinct
Perform 'dmst.test' on simulated datadmst.sim
Dynamic Minimum Spanning Tree spatial scan testdmst.test
Determine zones for the Dynamic Minimum Spanning Tree scan testdmst.zones
Perform 'edmst.test' on simulated dataedmst.sim
Early Stopping Dynamic Minimum Spanning Tree spatial scan testedmst.test
Determine zones for the early stopping dynamic Minimum Spanning Tree scan testedmst.zones
Compute Elbow Pointelbow_point
Nearest neighbors for elliptic scanelliptic.nn
Compute elliptic penaltyelliptic.penalty
Perform 'elliptic.test' on simulated dataelliptic.sim.adj
Elliptical Spatial Scan Testelliptic.test
Determine zones for 'elliptic.test'elliptic.zones
Perform 'fast.test' on simulated datafast.sim
Fast Subset Scan Testfast.test
Determine sequence of fast subset scan zonesfast.zones
Flexibly-shaped Spatial Scan Testflex_test
Determine zones for flexibly shaped spatial scan testflex_zones
Perform 'flex.test' on simualated dataflex.sim
Flexibly-shaped Spatial Scan Testflex.test
Determine zones for flexibly shaped spatial scan testflex.zones
Compute distance for geographic coordinateseucdist gcdist gedist
K nearest neighborsknn
Apply getElement over a listlget lgetElement sget sgetElement
Maxima Likelihood First Scan Testmlf.test
Determine zones for the maxima likelihood first algorithm.mlf.zones
Perform 'mlink.test' on simulated datamlink.sim
Maximum Linkage spatial scan testmlink.test
Determine zones for the Maximum Linkage scan testmlink.zones
Constant-risk Moran's I statisticmorancr.sim
Constant-risk Moran's I statisticmorancr.stat
Constant-risk Moran's I-based testmorancr.test
Minimum spanning tree for all regionsmst.all
Minimum spanning tree sequencemst.seq
Number of clustersnclusters
Breast cancer mortality in the Northeastern United Statesneast
Binary adjacency matrix for 'neast'neastw
Cumulative sum over nearest neighborsnn.cumsum
Convert nearest neighbors list to zonesnn2zones
Determine nearest neighbors based on maximum distancenndist
Determine duplicates in nearest neighbor listnndup
Determine nearest neighbors with population constraintnnpop scan.nn
Determine non-overlapping zonesnoz
Leukemia data for 281 regions in New York.nydf
'SpatialPolygons' object for New York leukemia data.nypoly
'sf' object for New York leukemia data.nysf
'SpatialPolygonsDataFrame' for New York leukemia data.nysp
Adjacency matrix for New York leukemia data.nyw
Optimal Population Upper Bound Statisticsoptimal_ubpop
Plot object of class 'smerc_cluster'.plot.smerc_cluster
Plot object of class 'smerc_optimal_ubpop'.plot.smerc_optimal_ubpop
Plots an object of class 'tango'.plot.tango
Perform 'precog.test' on simulated data.precog.sim
PreCoG Scan Testprecog.test
Print object of class 'smerc_cluster'.print.smerc_cluster
Print object of class 'smerc_optimal_ubpop'.print.smerc_optimal_ubpop
Print object of class 'smerc_similarity_test'.print.smerc_similarity_test
Print object of class 'tango'.print.tango
Determine zones for flexibly shaped spatial scan testrflex_zones
Compute middle p-valuerflex.midp
Perform 'rflex.test' on simualated datarflex.sim
Restricted Flexibly-shaped Spatial Scan Testrflex.test
Determine zones for flexibly shaped spatial scan testrflex.zones
Spatial scan statisticscan_stat stat_binom stat_poisson
Perform 'scan.test' on simulated datascan.sim.adj
Spatial scan statisticscan.stat stat.binom stat.poisson
Spatial Scan Testscan.test
Determine zones for the spatial scan testscan.zones
Return most significant, non-overlapping zonessig_noc
smercsmerc-package smerc
Prepare 'smerc_cluster'smerc_cluster
Summary of 'smerc_cluster' objectsummary.smerc_cluster
Tango's statistictango.stat
Tango's clustering detection testtango.test
Distance-based weights for 'tango.test'dweights tango.weights
Perform 'uls.test' on simulated datauls.sim
Upper Level Set Spatial Scan Testuls.test
Determine sequence of ULS zones.uls.zones
Sum over zoneszones.sum