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smacpod (version 2.6)

Statistical Methods for the Analysis of Case-Control Point Data

Description

Statistical methods for analyzing case-control point data. Methods include the ratio of kernel densities, the difference in K Functions, the spatial scan statistic, and q nearest neighbors of cases.

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Version

Install

install.packages('smacpod')

Monthly Downloads

771

Version

2.6

License

GPL (>= 2)

Maintainer

Joshua French

Last Published

September 22nd, 2023

Functions in smacpod (2.6)

plot.spscan

Plots object from spscan.test.
smacpod

smacpod
print.logrrenv

Print a logrrenv object
print.spscan

Plots object from spscan.test.
reexports

Objects exported from other packages
qnn.test

q Nearest Neighbors Test
print.kdplus_test

Print a kdplus_test object
print.logrr_test

Print a logrr_test object
spdensity

Kernel smoothed spatial density of point pattern
summary.kdenv

Summarize a kdenv object
spscan.test

Spatial Scan Test
summary.spscan

Summarize object from spscan.test.
kdplus.test

Global test of clustering using difference in K functions
kdest

Difference of estimated K functions
grave

Medieval Grave Site Data
clusters.spscan

Extract clusters
circles.plot

Plot circles
circles.intersect

Determine whether circles intersect
kd

Difference of estimated K functions
gradient.color.scale

Create gradient color scale with midpoint
arg_check_alternative

Argument check alternative
logrr

Log ratio of spatial densities
plot.logrrenv

Plots objects produced by the logrr function.
noc

Determine non-overlapping clusters
plot.kdenv

Plot a kdenv object.
logrr.test

Global test of clustering using log ratio of spatial densities
nn

Determine nearest neighbors
print.kdenv

Print a kdenv object
print.kdenv_summary

Print a kdenv_summary object