StatDA (version 1.7.11)

concarea: Plot Concentration Area

Description

Displays a concentration-area plot (see also concareaExampleKola). This function is preferable since it can be applied to non-Kola data!

Usage

concarea(x, y, z, zname = deparse(substitute(z)),
caname = deparse(substitute(z)), borders=NULL, 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))

Value

The concentration area plot, in both directions, is created.

Arguments

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

Author

Peter Filzmoser <> http://cstat.tuwien.ac.at/filz/

Details

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.

References

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.

See Also

concareaExampleKola

Examples

data(ohorizon)
data(kola.background)
data(bordersKola)

Cu=ohorizon[,"Cu"]
X=ohorizon[,"XCOO"]
Y=ohorizon[,"YCOO"]

op <- par(mfrow=c(1,2),mar=c(4,4,2,2))
concarea(X,Y,Cu,log=TRUE,zname="Cu in O-horizon [mg/kg]",borders="bordersKola", ifrev=FALSE,
         x.logfinetick=c(2,5,10),y.logfinetick=c(10))
par(op)