Statistical Methods for the Analysis of Case-Control Point Data
Argument check alternative
Determine whether circles intersect
Plot circles
Extract clusters
Create spscan object
Create gradient color scale with midpoint
Difference of estimated K functions
Difference of estimated K functions
Global test of clustering using difference in K functions
Log ratio of spatial densities
Global test of clustering using log ratio of spatial densities
Determine nearest neighbors
Determine non-overlapping clusters
Plot a kdenv object.
Plots objects produced by the logrrfunction.
Plots object from spscan.test.
Print a kdenv_summary object
Print a kdenv object
Print a kdplus_test object
Print a logrr_test object
Print a logrrenv object
Plots object from spscan.test.
q Nearest Neighbors Test
Objects exported from other packages
smacpod
Kernel smoothed spatial density of point pattern
Compute spatial scan statistics for simulated data
Compute spatial scan statistic
Spatial Scan Test
Summarize a kdenv object
Summarize object from spscan.test.
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.