Man pages for jfrench/smerc
Statistical Methods for Regional Counts
| all_shape_dists | Return all shapes and distances for each zone |
| arg_check_dist_ellipse | Check argments if dist.ellipse |
| 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 |
| csg | 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... |
| edmst.sim | Perform 'edmst.test' on simulated data |
| edmst.test | Early Stopping Dynamic Minimum Spanning Tree spatial scan... |
| edmst.zones | Determine zones for the early stopping dynamic Minimum... |
| elbow_point | Compute Elbow Point |
| elliptic.nn | Nearest neighbors for elliptic scan |
| elliptic.penalty | Compute elliptic penalty |
| elliptic.sim | Perform 'elliptic.test' on simulated data |
| 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.test | Flexibly-shaped Spatial Scan Test |
| flex_zones | Determine zones for 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 |
| logical2zones | Convert logical vector to zone |
| mc.pvalue | Compute Monte Carlo p-value |
| 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' |
| nn2zones | Convert nearest neighbors list to zones |
| nn.cumsum | Cumulative sum over nearest neighbors |
| nndist | Determine nearest neighbors based on maximum distance |
| nndup | Determine duplicates in nearest neighbor list |
| noc_enn | Returned ordered non-overlapping clusters |
| noc_nn | Returned ordered non-overlapping clusters |
| 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 |
| prep.mst | Return nicely formatted results from mst.all |
| 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.nn | Determine nearest neighbors with population constraint |
| scan.sim | Perform 'scan.test' on simulated data |
| scan.sim.adj | Perform 'scan.test' on simulated data |
| scan_stat | Spatial scan statistic |
| scan.stat | Spatial scan statistic |
| scan.test | Spatial Scan Test |
| scan.zones | Determine zones for the spatial scan test |
| seq_scan_sim | Perform scan test on simulated data sequentially |
| seq_scan_test | Sequential Scan Test |
| sig_noc | Return most significant, non-overlapping zones |
| sig_prune | Prune significant, non-overlapping zones |
| smerc | smerc |
| smerc_cluster | Prepare 'smerc_cluster' |
| stat.poisson.adj | Compute Poisson test statistic |
| 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. |
| w2segments | Returns segments connecting neighbors |
| zones.sum | Sum over zones |
