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smerc (version 1.0.1)

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

1.0.1

License

GPL (>= 2)

Maintainer

Joshua French

Last Published

July 15th, 2019

Functions in smerc (1.0.1)

Combine distinct zones

Elliptical Spatial Scan Test

Determine zones for elliptic.test

Construct connected subgraphs

Maxima Likelihood First Scan Test

Nearest neighbors for elliptic scan

Determine case windows (circles)

Perform elliptic.test on simulated data

arg_check_scan_test

Argument checking for many scan-like functions

Determine zones for the Maximum Linkage scan test

K nearest neighbors

Compute Monte Carlo p-value

Minimum spanning tree for all regions

Distinct elements of a list

Restricted Flexibly-shaped Spatial Scan Test

Determine nearest neighbors for minimum spanning trees

Perform rflex.test on simualated data

Determine zones for flexibly shaped spatial scan test

Perform fast.test on simulated data

Fast Subset Scan Test

Distance-based weights

Perform edmst.test on simulated data

Return nicely formatted results from mst.all

Perform dc.test on simulated data

Determine zones for the maxima likelihood first algorithm.

Dynamic Minimum Spanning Tree spatial scan test

Perform dmst.test on simulated data

Determine zones for the Dynamic Minimum Spanning Tree scan test

Perform flex.test on simualated data

Determine sequence of fast subset scan zones

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

Compute middle p-value

Convert nearest neighbors list to zones

Determine nearest neighbors based on maximum distance

Double Connection spatial scan test

Perform scan.test on simulated data

Spatial scan statistic

Prepare scan results

Maximum Linkage spatial scan test

Upper Level Set Spatial Scan Test

Perform mlink.test on simulated data

Perform uls.test on simulated data

Determine duplicates in nearest neighbor list

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

Early Stopping Dynamic Minimum Spanning Tree spatial scan test

Compute minor axis distance of ellipse

Determine zones for the Double Connected scan test

Flexibly-shaped Spatial Scan Test

Determine zones for flexibly shaped spatial scan test

Cumulative sum over nearest neighbors

Minimum spanning tree sequence

Plots object of class scan.

Plots an object of class tango.

Returns segments connecting neighbors

Tango's cluster detection test

Determine sequence of ULS zones.

Tango's statistic

Spatial Scan Test

SpatialPolygonsDataFrame for New York leukemia data.

Leukemia data for 281 regions in New York.

Adjacency matrix for New York leukemia data.

Determine zones for the spatial scan test

arg_check_dmst_zones

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

arg_check_dist_ellipse

Check argments if dist.ellipse

arg_check_tango_test

Argument checking for tango.test

Besag-Newell Test

arg_check_rflex_zones

Check arguments of rflex.zones

Argument checking for *.sim functions

arg_check_scan_zones

Argument checking for scan.zones

arg_check_bn_test

Argument checking for bn.test

all_shape_dists

Return all shapes and distances for each zone