Complete regular grid analysis

This function defines objects to analyse data sets associated with complete regular grid.

Usage

gridrowcol(nrow, ncol, cell.names = NULL)

Arguments

nrow: size of the grid (number of rows)
ncol: size of the grid (number of columns)
cell.names: grid cell labels

Value

Returns a list containing the following items :

xy: : a data frame with grid cell coordinates
area: : a data frame with three variables to display grid cells as areas
neig: : an object of class 'neig' corresponding to a neighbouring graph of the grid (rook case)
orthobasis: : an object of class 'orthobasis' corresponding to the analytical solution for the neighbouring graph

References

Méot, A., Chessel, D. and Sabatier, D. (1993) Opérateurs de voisinage et analyse des données spatio-temporelles. in J.D. Lebreton and B. Asselain, editors. Biométrie et environnement. Masson, 45-72.

Cornillon, P.A. (1998) Prise en compte de proximités en analyse factorielle et comparative. Thèse, Ecole Nationale Supérieure Agronomique, Montpellier.

Author

Sébastien Ollier sebastien.ollier@u-psud.fr
Daniel Chessel

Examples

w <- gridrowcol(8, 5)
par(mfrow = c(1, 2))
area.plot(w$area, center = w$xy, graph = w$neig, clab = 0.75)
area.plot(w$area, center = w$xy, graph = w$neig, clab = 0.75, label = as.character(1:40))

par(mfrow = c(1, 1))

if(adegraphicsLoaded()) {
  fac1 <- w$orthobasis
  names(fac1) <- as.character(signif(attr(w$orthobasis, "values"), 3))
  s.value(w$xy, fac1, porigin.include = FALSE, plegend.drawKey = FALSE, pgrid.text.cex = 0,
    ylim = c(0, 10))

} else {
  par(mfrow = c(5,8))
  for(k in 1:39)
    s.value(w$xy, w$orthobasis[, k], csi = 3, cleg = 0, csub = 2,
     sub = as.character(signif(attr(w$orthobasis, "values")[k], 3)),
      incl = FALSE, addax = FALSE, cgr = 0, ylim = c(0,10))
  par(mfrow = c(1,1))
}