The function takes a list
polygons and draws the corresponding map. Different
colors for each polygon can be used. Typically used for objects of class "mrf.bayesx"
and
"random.bayesx"
returned from function bayesx
and
read.bayesx.output
.
1 2 3 4 5 6 7 8  plotmap(map, x = NULL, id = NULL, c.select = NULL, legend = TRUE,
missing = TRUE, swap = FALSE, range = NULL, names = FALSE,
values = FALSE, col = NULL, ncol = 100, breaks = NULL,
cex.legend = 1, cex.names = 1, cex.values = cex.names, digits = 2L,
mar.min = 2, add = FALSE, interp = FALSE, grid = 200,
land.only = FALSE, extrap = FALSE, outside = FALSE, type = "akima",
linear = FALSE, k = 40, p.pch = 15, p.cex = 1, shift = NULL,
trans = NULL, ...)

map 
the map to be plotted, the map object must be a 
x 
a matrix or data frame with two columns, first column indicates the region and
second column the the values which will define the background colors of the polygons, e.g.
fitted values from 
id 
if argument 
c.select 
select the column of the data in 
legend 
if set to 
missing 
should polygons be plotted for which no data is available in 
swap 
if set to 
range 
specify the range of values in 
names 
if set to 
values 
if set to 
col 
the color of the surface, may also be a function, e.g.

ncol 
the number of different colors that should be generated if 
breaks 
a set of breakpoints for the colors: must give one more breakpoint than

cex.legend 
text size of the numbers in the legend. 
cex.names 
text size of the names if 
cex.values 
text size of the names if 
digits 
specifies the legend decimal places. 
mar.min 
Controls the definition of boundaries. Could be either 
add 
if set to 
interp 
logical. Should the values provided in argument 
grid 
integer. Defines the number of grid cells to be used for interpolation. 
land.only 
if set to 
extrap 
logical. Should interpolations be computed outside the observation area (i.e., extrapolated)? 
outside 
logical. Should interpolated values outside the boundaries of the map be plotted. 
type 
character. Which type of interpolation metjod should be used. The default is

linear 
logical. Should linear interpolation be used withing function

k 
integer. The number of basis functions to be used to compute the interpolated surface
when 
p.pch 
numeric. The point size of the grid cells when using interpolation. 
p.cex 
numeric. The size of the grid cell points whein using interpolation. 
shift 
numeric. Constant to be added to the smooth before plotting. 
trans 
function to be applied to the smooth before plotting, e.g., to transform the plot to the response scale. 
... 
parameters to be passed to 
Function plotmap
uses per default the akima package to construct smooth interpolated
surfaces, therefore, package akima needs to be installed. The akima package has an ACM
license that restricts applications to noncommercial usage, see
http://www.acm.org/publications/policies/softwarecrnotice
Function plotmap
prints a note refering to the ACM licence. This note can be supressed by
setting
options("use.akima" = TRUE)
Nikolaus Umlauf, Thomas Kneib, Stefan Lang, Achim Zeileis.
plot.bayesx
, read.bnd
, colorlegend
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131  ## load a sample map
data("FantasyBnd")
## plot the map
op < par(no.readonly = TRUE)
plotmap(FantasyBnd, main = "Example of a plain map")
plotmap(FantasyBnd, lwd = 1, main = "Example of a plain map")
plotmap(FantasyBnd, lwd = 1, lty = 2)
plotmap(FantasyBnd, lwd = 1, lty = 2, border = "green3")
plotmap(FantasyBnd, lwd = 1, lty = 2, border = "green3",
density = 50)
plotmap(FantasyBnd, lwd = 1, lty = 2,
border = c("red", "green3"),
density = c(10, 20), angle = c(5, 45))
plotmap(FantasyBnd, lwd = 1, lty = 2,
border = c("red", "green3"),
density = c(10, 20), angle = c(5, 45),
col = c("blue", "yellow"))
plotmap(FantasyBnd, col = gray.colors(length(FantasyBnd)))
## add some values to the corresponding polygon areas
## note that the first column in matrix val contains
## the region identification index
x < cbind(as.integer(names(FantasyBnd)), runif(length(FantasyBnd), 2, 2))
plotmap(FantasyBnd, x = x)
## now only plot values for some certain regions
set.seed(432)
samps < sample(x[,1], 4)
nx < x[samps,]
plotmap(FantasyBnd, x = nx, density = 20)
## play with legend
plotmap(FantasyBnd, x = x, names = TRUE, legend = FALSE)
plotmap(FantasyBnd, x = nx, density = 20, pos = c(0, 1))
plotmap(FantasyBnd, x = nx, density = 20, pos = c(0, 0.8),
side.legend = 2)
plotmap(FantasyBnd, x = nx, density = 20, pos = c(0, 0.8),
side.legend = 2, side.tick = 2)
plotmap(FantasyBnd, x = nx, density = 20, pos = c(0, 0.8),
side.legend = 2, side.tick = 2, cex.legend = 0.5)
plotmap(FantasyBnd, x = x, values = TRUE,
pos = c(0.15, 0.12))
plotmap(FantasyBnd, x = nx, values = TRUE,
pos = c(0.07, 0.22), width = 2,
at = nx[,2], side.legend = 2, distance.labels = 3,
density = 20)
plotmap(FantasyBnd, x = nx, values = TRUE,
pos = c(0.07, 0.22), width = 2,
at = nx[,2], side.legend = 2, distance.labels = 3,
density = 20, symmetric = FALSE,
col = heat_hcl, swap = TRUE)
plotmap(FantasyBnd, x = nx, values = TRUE,
pos = c(0.07, 0.22), width = 2,
at = nx[,2], side.legend = 2, distance.labels = 3,
density = 20, symmetric = FALSE,
col = heat_hcl, swap = TRUE, range = c(5, 5))
plotmap(FantasyBnd, x = nx, values = TRUE,
pos = c(0.07, 0.22), width = 2,
at = nx[,2], side.legend = 2, distance.labels = 3,
density = 20, symmetric = FALSE,
col = heat_hcl, swap = TRUE, lrange = c(5, 5))
plotmap(FantasyBnd, x = nx, values = TRUE,
pos = c(0.07, 0.22), width = 2,
at = nx[,2], side.legend = 2, distance.labels = 3,
density = 20, symmetric = FALSE,
col = heat_hcl, swap = TRUE,
ncol = 4, breaks = seq(2, 2, length = 5))
## more position options
plotmap(FantasyBnd, x = nx, density = 20, pos = "bottomleft")
plotmap(FantasyBnd, x = nx, density = 20, pos = "topleft")
plotmap(FantasyBnd, x = nx, density = 20, pos = "topright")
plotmap(FantasyBnd, x = nx, density = 20, pos = "bottomright")
plotmap(FantasyBnd, x = nx, density = 20, pos = "right")
par(op)
# load and plot a map from GermanyBnd
op < par(no.readonly = TRUE)
data("GermanyBnd")
plotmap(GermanyBnd, main = "Map of GermanyBnd")
n < length(GermanyBnd)
# add some colors
plotmap(GermanyBnd, col = rainbow(n))
plotmap(GermanyBnd, col = heat.colors(n))
plotmap(GermanyBnd, col = topo.colors(n))
plotmap(GermanyBnd, col = cm.colors(n))
plotmap(GermanyBnd, col = gray.colors(n))
plotmap(GermanyBnd, col = c("green", "green3"))
par(op)
## now with bayesx
set.seed(333)
## simulate some geographical data
data("MunichBnd")
N < length(MunichBnd); names(MunichBnd) < 1:N
n < N*5
## regressors
dat < data.frame(id = rep(1:N, n/N))
dat$sp < with(dat, sort(runif(N, 2, 2), decreasing = TRUE)[id])
## response
dat$y < with(dat, 1.5 + sp + rnorm(n, sd = 0.6))
## Not run:
## estimate model
b < bayesx(y ~ sx(id, bs = "mrf", map = MunichBnd),
method = "MCMC", data = dat)
## summary statistics
summary(b)
## plot spatial effect
op < par(no.readonly = TRUE)
plot(b, map = MunichBnd)
plot(b, map = MunichBnd, c.select = "97.5
plot(b, map = MunichBnd, c.select = "2.5
plot(b, map = MunichBnd, c.select = "50
plot(b, map = MunichBnd, names = TRUE,
cex.names = 0.5, cex.legend = 0.8)
plot(b, map = MunichBnd, range = c(0.5, 0.5))
plot(b, map = MunichBnd, range = c(5, 5))
plot(b, map = MunichBnd, col = heat_hcl,
swap = TRUE, symmetric = FALSE)
par(op)
## End(Not run)

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