• using R Under development (unstable) (2025-11-23 r89052)
• using platform: x86_64-pc-linux-gnu
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• running under: Debian GNU/Linux forky/sid
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• this is package ‘echelon’ version ‘0.4.0’
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[2s/2s] ERROR Running examples in ‘echelon-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: echebin > ### Title: Echelon spatial scan statistic based on Binomial model > ### Aliases: echebin > ### Keywords: echelon analysis spatial scan statistic spatial cluster > ### deteciotn > > ### ** Examples > > ##Hotspot detection for non-white birth in North Carolina using echelon scan > > #Load required packages and data > library(spData) To access larger datasets in this package, install the spDataLarge package with: `install.packages('spDataLarge', repos='https://nowosad.github.io/drat/', type='source')` > data("nc.sids") > > #Non-white birth from 1974 to 1984 (case data) > nwb <- nc.sids$NWBIR74 + nc.sids$NWBIR79 > > #White birth from 1974 to 1984 (control data) > wb <- (nc.sids$BIR74 - nc.sids$NWBIR74) + (nc.sids$BIR79 - nc.sids$NWBIR79) > > ##Hotspot detection based on Binomial model > #Echelon analysis > SIDS.echelon <- echelon(x = nwb/wb, nb = ncCR85.nb, name = row.names(nc.sids)) 19 echelons are created See the objects 'Table' and 'Echelons' for more details > > #Basic cluster detection (significance not evaluated) > SIDS.clusters <- echebin(SIDS.echelon, cas = nwb, ctl = wb, K = 20, + n.sim = 0, cluster.info = TRUE, main = "Hgih rate clusters", ens = FALSE) dev.new(): using pdf(file="Rplots1.pdf") ------------- CLUSTERS DETECTED ------------- Number of locations ......: 100 region Limit length of cluster ..: 20 regions Total cases ..............: 240380 Total population .........: 752354 Scan for Area with .......: High Rates Number of Replications ...: 0 Model ....................: Binomial --------------------------------------------- MOST LIKELY CLUSTER -- 20 regions  Cluster regions included : Halifax, Gates, Edgecombe, Martin, Washington, Vance, Chowan, Granville, Franklin, Greene, Lenoir, Northampton, Bertie, Hertford, Warren, Wilson, Jones, Pitt, Durham, Perquimans  Population ..............: 98424  Number of cases .........: 54019  Expected cases ..........: 31446.847  Observed / expected .....: 1.7178  Relative risk ...........: 1.9258  Log likelihood ratio ....: 12804.6298 ---------------------------------------------- SECONDARY CLUSTERS 2 -- 3 regions  Cluster regions included : Robeson, Hoke, Scotland  Population ..............: 25048  Number of cases .........: 17604  Expected cases ..........: 8002.9324  Observed / expected .....: 2.1997  Relative risk ...........: 2.2945  Log likelihood ratio ....: 8004.2121 3 -- 1 regions  Cluster regions included : Anson  Population ..............: 3445  Number of cases .........: 2113  Expected cases ..........: 1100.6908  Observed / expected .....: 1.9197  Relative risk ...........: 1.9279  Log likelihood ratio ....: 628.1941 4 -- 1 regions  Cluster regions included : Mecklenburg  Population ..............: 52345  Number of cases .........: 19658  Expected cases ..........: 16724.4291  Observed / expected .....: 1.1754  Relative risk ...........: 1.191  Log likelihood ratio ....: 396.0322 5 -- 1 regions  Cluster regions included : Caswell  Population ..............: 2288  Number of cases .........: 1147  Expected cases ..........: 731.0248  Observed / expected .....: 1.569  Relative risk ...........: 1.5718  Log likelihood ratio ....: 162.5374 ---------------------------------------------- Display only the top 5 clusters. See object 'clusters' for more details > text(SIDS.echelon$coord, labels = SIDS.echelon$regions.name, + adj = -0.1, cex = 0.7) > > #Detected clusters and neighbors map > #XY coordinates of each polygon centroid point > NC.coo <- cbind(nc.sids$lon, nc.sids$lat) > echebin(SIDS.echelon, cas = nwb, ctl = wb, K = 20, + n.sim = 0, coo = NC.coo, dendrogram = FALSE) dev.new(): using pdf(file="Rplots2.pdf") MOST LIKELY CLUSTER -- 20 regions  Cluster regions included : Halifax, Gates, Edgecombe, Martin, Washington, Vance, Chowan, Granville, Franklin, Greene, Lenoir, Northampton, Bertie, Hertford, Warren, Wilson, Jones, Pitt, Durham, Perquimans  Population ..............: 98424  Number of cases .........: 54019  Expected cases ..........: 31446.847  Observed / expected .....: 1.7178  Relative risk ...........: 1.9258  Log likelihood ratio ....: 12804.6298 > > #Load geospatial information for North Carolina > nc <- sf::st_read(system.file("shape/nc.shp", package = "sf")) Reading layer `nc' from data source   `/home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/sf/shape/nc.shp'   using driver `ESRI Shapefile' Simple feature collection with 100 features and 14 fields Geometry type: MULTIPOLYGON Dimension: XY Bounding box: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965 Geodetic CRS: NAD27 > > #Extract detected clusters > MLC <- SIDS.clusters$clusters[[1]] > Secondary <- SIDS.clusters$clusters[[2]] > > #Assign colors to clusters for plotting > cluster.col <- rep(0, length(nwb)) > cluster.col[MLC$regionsID] <- 2 > cluster.col[Secondary$regionsID] <- 3 > > #Plot detected high-rate clusters on a simple map > plot(nc$geom, col = cluster.col, + main = "Detected high rate clusters") > legend("bottomleft", + legend = c( + paste("1- p-value:", MLC$p), + paste("2- p-value:", Secondary$p) + ), + text.col = c(2, 3) + ) > > #Interactive map visualization with mapview > library(mapview) Error in library(mapview) : there is no package called ‘mapview’ Execution halted
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Status: 1 ERROR