irishdata: Geary's Irish Data

In ade4: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

Geary's Irish Data

Description

This data set contains geographical informations about 25 counties of Ireland.

Usage

data(irishdata)

Format

irishdata is a list of 13 components:

area

a data frame with polygons for each of the 25 contiguous counties

county.names

a vector with the names of the 25 counties

xy

a data frame with the coordinates centers of the 25 counties

tab

a data frame with 25 rows (counties) and 12 variables

contour

a data frame with the global polygon of all the 25 counties

link

a matrix containing the common length between two counties from area

area.utm

a data frame with polygons for each of the 25 contiguous counties expressed in Universal Transverse Mercator (UTM) coordinates

xy.utm

a data frame with the UTM coordinates centers of the 25 counties

link.utm

a matrix containing the common length between two counties from area.utm

tab.utm

a data frame with the 25 counties (explicitly named) and 12 variables

contour.utm

a data frame with the global polygon of all the 25 counties expressed in UTM coordinates

Spatial

the map of the 25 counties of Ireland (an object of the class SpatialPolygons of sp)

Spatial.contour

the contour of the map of the 25 counties of Ireland (an object of the class SpatialPolygons of sp)

Source

Geary, R.C. (1954) The contiguity ratio and statistical mapping. The incorporated Statistician, 5, 3, 115–145.

Cliff, A.D. and Ord, J.K. (1973) Spatial autocorrelation, Pion, London. 1–178.

Examples

data(irishdata)

if(adegraphicsLoaded()) {

  if(requireNamespace("sp", quietly = TRUE)){
  g1 <- s.label(irishdata$xy.utm, Sp = irishdata$Spatial, pSp.col = "white", plot = FALSE)
  
  g21 <- s.label(irishdata$xy.utm, Sp = irishdata$Spatial, pSp.col = "white", plab.cex = 0, 
    ppoints.cex = 0, plot = FALSE)
  g22 <- s.label(irishdata$xy.utm, Sp = irishdata$Spatial.contour, pSp.col = "transparent", 
    plab.cex = 0, ppoints.cex = 0, pSp.lwd = 3, plot = FALSE)
  g2 <- superpose(g21, g22)   

  g3 <- s.corcircle(dudi.pca(irishdata$tab, scan = FALSE)$co, plot = FALSE)
  
  score <- dudi.pca(irishdata$tab, scannf = FALSE, nf = 1)$li$Axis1
  names(score) <- row.names(irishdata$Spatial)
  
  obj <- sp::SpatialPolygonsDataFrame(Sr = irishdata$Spatial, data = as.data.frame(score))
  g4 <- s.Spatial(obj, plot = FALSE)
  
  G <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))
  }
  
} else {
  par(mfrow = c(2, 2))
  area.plot(irishdata$area, lab = irishdata$county.names, clab = 0.75)
  area.plot(irishdata$area)
  apply(irishdata$contour, 1, function(x) segments(x[1], x[2], x[3], x[4], lwd = 3))
  s.corcircle(dudi.pca(irishdata$tab, scannf = FALSE)$co)
  score <- dudi.pca(irishdata$tab, scannf = FALSE, nf = 1)$li$Axis1
  names(score) <- row.names(irishdata$tab)
  area.plot(irishdata$area, score)
  par(mfrow = c(1, 1))
}

ade4 documentation built on Feb. 16, 2023, 7:58 p.m.