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smerc (version 1.1)

Statistical Methods for Regional Counts

Description

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, first introduced by Kulldorff and Nagarwalla (1995) and Kulldorff (1997) .

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Version

Install

install.packages('smerc')

Monthly Downloads

1,190

Version

1.1

License

GPL (>= 2)

Maintainer

Joshua French

Last Published

September 19th, 2019

Functions in smerc (1.1)

Perform dc.test on simulated data

Double Connection spatial scan test

arg_check_dist_ellipse

Check argments if dist.ellipse

Besag-Newell Test

Distinct elements of a list

Perform dmst.test on simulated data

Determine case windows (circles)

Combine distinct zones

Construct connected subgraphs

Distance-based weights

Compute region weights for cepp.test

Perform cepp.test on simulated data

Determine zones for the Double Connected scan test

Determine sequence of fast subset scan zones

Compute minor axis distance of ellipse

Cluster Evalation Permutation Procedure Test

Perform edmst.test on simulated data

Fast Subset Scan Test

Perform fast.test on simulated data

Plots object of class scan.

Elliptical Spatial Scan Test

Determine zones for elliptic.test

Perform flex.test on simualated data

Maxima Likelihood First Scan Test

Plots an object of class tango.

Determine nearest neighbors with population constraint

Determine zones for flexibly shaped spatial scan test

Dynamic Minimum Spanning Tree spatial scan test

Minimum spanning tree sequence

Cumulative sum over nearest neighbors

K nearest neighbors

Compute Monte Carlo p-value

Early Stopping Dynamic Minimum Spanning Tree spatial scan test

Determine zones for the maxima likelihood first algorithm.

Leukemia data for 281 regions in New York.

Determine duplicates in nearest neighbor list

Determine zones for the Dynamic Minimum Spanning Tree scan test

Determine zones for the early stopping dynamic Minimum Spanning Tree scan test

Prepare scan results

Return nicely formatted results from mst.all

Flexibly-shaped Spatial Scan Test

Determine zones for the spatial scan test

Perform uls.test on simulated data

Spatial Scan Test

Perform rflex.test on simualated data

Determine zones for flexibly shaped spatial scan test

Restricted Flexibly-shaped Spatial Scan Test

Nearest neighbors for elliptic scan

Determine zones for the Maximum Linkage scan test

Minimum spanning tree for all regions

Determine sequence of ULS zones.

Upper Level Set Spatial Scan Test

SpatialPolygonsDataFrame for New York leukemia data.

Adjacency matrix for New York leukemia data.

Returns segments connecting neighbors

Convert nearest neighbors list to zones

Perform elliptic.test on simulated data

Determine nearest neighbors based on maximum distance

Perform scan.test on simulated data

Spatial scan statistic

Perform mlink.test on simulated data

Maximum Linkage spatial scan test

Tango's statistic

Tango's cluster detection test

Compute middle p-value

a simplified prep.scan for non-scan methods orders on p-value instead of test statistic

arg_check_rflex_zones

Check arguments of rflex.zones

arg_check_bn_test

Argument checking for bn.test

all_shape_dists

Return all shapes and distances for each zone

arg_check_dmst_zones

Argument checking for dmst.zones, dc.zones, and mlink.zones functions

arg_check_tango_test

Argument checking for tango.test

arg_check_cepp_test

Argument checking for cepp.test

Argument checking for *.sim functions

arg_check_scan_test

Argument checking for many scan-like functions

arg_check_scan_zones

Argument checking for scan.zones