Dynamic Minimum Spanning Tree spatial scan test
Determine zones for elliptic.test
Early Stopping Dynamic Minimum Spanning Tree spatial scan
test
Perform fast.test on simulated data
Nearest neighbors for elliptic scan
Compute Elbow Point
Elliptical Spatial Scan Test
Determine zones for flexibly shaped spatial scan test
Flexibly-shaped Spatial Scan Test
Perform flex.test on simualated data
Perform elliptic.test on simulated data
Compute distance for geographic coordinates
Determine zones for flexibly shaped spatial scan test
Determine sequence of fast subset scan zones
Determine zones for the early stopping dynamic Minimum
Spanning Tree scan test
Flexibly-shaped Spatial Scan Test
Fast Subset Scan Test
Perform edmst.test on simulated data
Apply getElement over a list
Perform elliptic.test on simulated data
K nearest neighbors
Compute elliptic penalty
Perform mlink.test on simulated data
Determine zones for the maxima likelihood
first algorithm.
Maxima Likelihood First Scan Test
Convert logical vector to zone
Determine duplicates in nearest neighbor list
Compute Monte Carlo p-value
Number of clusters
Maximum Linkage spatial scan test
Constant-risk Moran's I statistic
Determine zones for the Maximum Linkage scan test
Minimum spanning tree for all regions
Leukemia data for 281 regions in New York.
Returned ordered non-overlapping clusters
Convert nearest neighbors list to zones
Constant-risk Moran's I statistic
Breast cancer mortality in the Northeastern United States
Minimum spanning tree sequence
SpatialPolygons object for New York
leukemia data.
sf object for New York leukemia data.
SpatialPolygonsDataFrame for New York
leukemia data.
Print object of class smerc_cluster.
print.smerc_optimal_ubpop
Print object of class smerc_optimal_ubpop.
Tango's statistic
Spatial scan statistic
Spatial Scan Test
Tango's clustering detection test
Determine non-overlapping zones
Returned ordered non-overlapping clusters
Determine nearest neighbors based on maximum distance
Plot object of class smerc_cluster.
Determine zones for flexibly shaped spatial scan test
Restricted Flexibly-shaped Spatial Scan Test
Constant-risk Moran's I-based test
Cumulative sum over nearest neighbors
Binary adjacency matrix for neast
Plot object of class smerc_optimal_ubpop.
PreCoG Scan Test
Adjacency matrix for New York leukemia data.
Compute middle p-value
Determine zones for the spatial scan test
Return nicely formatted results from mst.all
Spatial scan statistic
Optimal Population Upper Bound Statistics
Return most significant, non-overlapping zones
Plots an object of class tango.
Prune significant, non-overlapping zones
Perform rflex.test on simualated data
Perform scan test on simulated data sequentially
Perform precog.test on simulated data.
Sequential Scan Test
Perform scan.test on simulated data
Perform scan.test on simulated data
Determine zones for flexibly shaped spatial scan test
Perform uls.test on simulated data
Distance-based weights for tango.test
print.smerc_similarity_test
Print object of class smerc_similarity_test.
Print object of class tango.
smerc
Determine nearest neighbors with population constraint
Sum over zones
Prepare smerc_cluster
Returns segments connecting neighbors
Compute Poisson test statistic
Summary of smerc_cluster object
Upper Level Set Spatial Scan Test
Determine sequence of ULS zones.
Besag-Newell Test
Determine case windows (circles)
Check argments if dist.ellipse
Return all shapes and distances for each zone
Perform cepp.test on simulated data
Determine zones for the Dynamic Minimum Spanning Tree scan test
Cluster Evalation Permutation Procedure Test
Determine zones for the Double Connected scan test
Double Connection spatial scan test
Perform dmst.test on simulated data
Combine distinct zones
Construct connected subgraphs
Perform dc.test on simulated data
Color clusters
Compute region weights for cepp.test
Compute minor axis distance of ellipse
Extract clusters
Distinct elements of a list