Concentration Area Plot for Kola data example
Displays a concentration area plot example for the Kola data. This procedure ist useful for determining if mulitple populations that are spatially dependent are present in a data set. For a more general function see concarea.
concareaExampleKola(x, y, z, zname = deparse(substitute(z)), caname = deparse(substitute(z)), borders="bordersKola", logx = FALSE, ifjit = FALSE, ifrev = FALSE, ngrid = 100, ncp = 0, xlim = NULL, xcoord = "Easting", ycoord = "Northing", ifbw = FALSE, x.logfinetick = c(2, 5, 10), y.logfinetick = c(2, 5, 10))
x |
name of the x-axis spatial coordinate, the eastings |
y |
name of the y-axis spatial coordinate, the northings |
z |
name of the variable to be processed and plotted |
zname |
a title for the x-axes of the qp-plot and concentration area plot. |
caname |
a title for the image of interpolated data. |
borders |
either NULL or character string with the name of the list with list elements x and y for x- and y-coordinates of map borders |
logx |
if it is required to make a logarithmis data transformation for the interpolation |
ifrev |
if FALSE the empirical function ist plotted from highest value to lowest |
ngrid |
default value is 100 |
xlim |
the range for the x-axis |
xcoord |
a title for the x-axis, defaults to "Easting" |
ycoord |
a title for the y-axis, defaults to "Northing" |
ifbw |
if the plot is drawn in black and white |
x.logfinetick |
how fine are the tick marks on log-scale on x-axis |
y.logfinetick |
how fine are the tick marks on log-scale on y-axis |
ifjit |
default value is FALSE |
ncp |
default value is 0 |
The function assumes that the area is proportional to the count of grid points. To be a reasonable model the data points should be 'evenly' spread over the plane. The interpolated grid size ist computed as (max(x) - min(x))/ngrid, with a default value of 100 for ngrid. Akima's interpolation function is used to obtain a linear interpolation between the spatial data values.
An example concentration area plot for Kola is created.
Peter Filzmoser <P.Filzmoser@tuwien.ac.at> http://cstat.tuwien.ac.at/filz/
C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter: Statistical Data Analysis Explained. Applied Environmental Statistics with R. John Wiley and Sons, Chichester, 2008.
data(ohorizon) data(kola.background) data(bordersKola) Cu=ohorizon[,"Cu"] X=ohorizon[,"XCOO"] Y=ohorizon[,"YCOO"] par(mfrow=c(2,2),mar=c(1.5,1.5,1.5,1.5)) concareaExampleKola(X,Y,Cu,log=TRUE,zname="Cu in O-horizon [mg/kg]", x.logfinetick=c(2,5,10),y.logfinetick=c(10))
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