an object containing the polygon information for the area
object
are either the values to plot in the draw.polys() function or a polygons information for a shape file for function polys2polys
scheme
scheme of colours to use, it can be "heat", "rainbow", "terrain", "topo", "cm" or any colour
swapcolors
to reverse the colours, it just work for "heat", "rainbow", "terrain", "topo", "cm" options
n.col
range for the colours
neighbour.nb
neighbour information for a shape file for function nb2nb
neighbour
the neighbour information, and if the neighbour is from S4 shape file than use nb2nb to transfer it to the appropriate neighbour for MRF(), MRFA(), mrf() and mrfa().
x
the factor defining the areas
area
all possible areas involved
...
for extra options
Details
draw.polys() plots the fitted values of fitted MRF object.
polys2nb() gets the neighbour information from the polygons.
nb2prec() creates the precision matrix from the neighbour information.
polys2polys() transforms a shape file polygons (S4 object) to the polygons required form for the functions MRF() and MRFA().
nb2nb() transforms from a shape file neighbour (S4 object) to the neighbour required form for functions MRF().
Value
The draw.polys() produces a plot while the rest of the functions produce required object for fitting or plotting.
Author(s)
Fernanda De Bastiani, Mikis Stasinopoulos, Robert Rigby and Vlasios Voudouris
Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion),
Appl. Statist., 54, part 3, pp 507-554.
Rue and Held (2005) Gaussian markov random fields: theory and applications, Chapman & Hall, USA.
Stasinopoulos D. M., Rigby R.A. and Akantziliotou C. (2006) Instructions on how to use the GAMLSS package in R.
Accompanying documentation in the current GAMLSS help files, (see also http://www.gamlss.org/).
Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R.
Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, http://www.jstatsoft.org/v23/i07.
See Also
MRF, MRFA
Examples
# bringing required libraries
library(spdep)
library(maptools)
# reading the shape file
bh <- readShapePoly(system.file("etc/shapes/bhicv.shp",package="spdep")[1])
# pick up part of the data
BhData <- data.frame(scale(bh@data[,5:8]))
# getting the neiboiurhood and the polygons using the spdep functions
bh.nb=poly2nb(bh)
bh.polys=bh@polygons
# now getting the information for the S4 object to required format
newpolys <- polys2polys(bh.polys,bh.nb)
newnb <- nb2nb(bh.nb)
# drawing the map
draw.polys(newpolys[[1]])
# now get the precition matrix
Prec <- nb2prec(newnb, x=as.factor(row.names(BhData)), area=as.factor(row.names(BhData)))