bn.test                 Besag-Newell Test
bn.zones                Determine case windows (circles)
cepp.sim                Perform 'cepp.test' on simulated data
cepp.test               Cluster Evalation Permutation Procedure Test
cepp.weights            Compute region weights for 'cepp.test'
clusters                Extract clusters
color.clusters          Color clusters
combine.zones           Combine distinct zones
csg2                    Construct connected subgraphs
dc.sim                  Perform 'dc.test' on simulated data
dc.test                 Double Connection spatial scan test
dc.zones                Determine zones for the Double Connected scan
                        test
dist.ellipse            Compute minor axis distance of ellipse
distinct                Distinct elements of a list
dmst.sim                Perform 'dmst.test' on simulated data
dmst.test               Dynamic Minimum Spanning Tree spatial scan test
dmst.zones              Determine zones for the Dynamic Minimum
                        Spanning Tree scan test
edmst.sim               Perform 'edmst.test' on simulated data
edmst.test              Early Stopping Dynamic Minimum Spanning Tree
                        spatial scan test
edmst.zones             Determine zones for the early stopping dynamic
                        Minimum Spanning Tree scan test
elbow_point             Compute Elbow Point
elliptic.nn             Nearest neighbors for elliptic scan
elliptic.penalty        Compute elliptic penalty
elliptic.sim.adj        Perform 'elliptic.test' on simulated data
elliptic.test           Elliptical Spatial Scan Test
elliptic.zones          Determine zones for 'elliptic.test'
fast.sim                Perform 'fast.test' on simulated data
fast.test               Fast Subset Scan Test
fast.zones              Determine sequence of fast subset scan zones
flex.sim                Perform 'flex.test' on simualated data
flex.test               Flexibly-shaped Spatial Scan Test
flex.zones              Determine zones for flexibly shaped spatial
                        scan test
flex_test               Flexibly-shaped Spatial Scan Test
flex_zones              Determine zones for flexibly shaped spatial
                        scan test
gedist                  Compute distance for geographic coordinates
knn                     K nearest neighbors
lget                    Apply getElement over a list
mlf.test                Maxima Likelihood First Scan Test
mlf.zones               Determine zones for the maxima likelihood first
                        algorithm.
mlink.sim               Perform 'mlink.test' on simulated data
mlink.test              Maximum Linkage spatial scan test
mlink.zones             Determine zones for the Maximum Linkage scan
                        test
morancr.sim             Constant-risk Moran's I statistic
morancr.stat            Constant-risk Moran's I statistic
morancr.test            Constant-risk Moran's I-based test
mst.all                 Minimum spanning tree for all regions
mst.seq                 Minimum spanning tree sequence
nclusters               Number of clusters
neast                   Breast cancer mortality in the Northeastern
                        United States
neastw                  Binary adjacency matrix for 'neast'
nn.cumsum               Cumulative sum over nearest neighbors
nn2zones                Convert nearest neighbors list to zones
nndist                  Determine nearest neighbors based on maximum
                        distance
nndup                   Determine duplicates in nearest neighbor list
nnpop                   Determine nearest neighbors with population
                        constraint
noz                     Determine non-overlapping zones
nydf                    Leukemia data for 281 regions in New York.
nypoly                  'SpatialPolygons' object for New York leukemia
                        data.
nysf                    'sf' object for New York leukemia data.
nysp                    'SpatialPolygonsDataFrame' for New York
                        leukemia data.
nyw                     Adjacency matrix for New York leukemia data.
optimal_ubpop           Optimal Population Upper Bound Statistics
plot.smerc_cluster      Plot object of class 'smerc_cluster'.
plot.smerc_optimal_ubpop
                        Plot object of class 'smerc_optimal_ubpop'.
plot.tango              Plots an object of class 'tango'.
precog.sim              Perform 'precog.test' on simulated data.
precog.test             PreCoG Scan Test
print.smerc_cluster     Print object of class 'smerc_cluster'.
print.smerc_optimal_ubpop
                        Print object of class 'smerc_optimal_ubpop'.
print.smerc_similarity_test
                        Print object of class 'smerc_similarity_test'.
print.tango             Print object of class 'tango'.
rflex.midp              Compute middle p-value
rflex.sim               Perform 'rflex.test' on simualated data
rflex.test              Restricted Flexibly-shaped Spatial Scan Test
rflex.zones             Determine zones for flexibly shaped spatial
                        scan test
rflex_zones             Determine zones for flexibly shaped spatial
                        scan test
scan.sim.adj            Perform 'scan.test' on simulated data
scan.stat               Spatial scan statistic
scan.test               Spatial Scan Test
scan.zones              Determine zones for the spatial scan test
scan_stat               Spatial scan statistic
sig_noc                 Return most significant, non-overlapping zones
smerc                   smerc
smerc_cluster           Prepare 'smerc_cluster'
summary.smerc_cluster   Summary of 'smerc_cluster' object
tango.stat              Tango's statistic
tango.test              Tango's clustering detection test
tango.weights           Distance-based weights for 'tango.test'
uls.sim                 Perform 'uls.test' on simulated data
uls.test                Upper Level Set Spatial Scan Test
uls.zones               Determine sequence of ULS zones.
zones.sum               Sum over zones
