angleplotmap {GeoXp}R Documentation

Detection of an eventual directional trend

Description

The function angleplotmap() is used to detect an eventual directional trend associated to variable var. It represents the absolute difference between the value of var at two sites as a function of the angle between vector vector(s_is_j) and the x-axis.

Usage

angleplotmap(long, lat, var, quantiles=NULL,listvar=NULL, listnomvar=NULL,
criteria=NULL,carte = NULL, label = "", cex.lab=1, pch = 16,col="blue",
xlab = "angle",ylab="absolut magnitude",lablong = "", lablat = "", axes=FALSE) 

Arguments

long a vector x of size n
lat a vector y of size n
var a vector of numeric values of size n
quantiles list of values of quantile orders (the regression quantile is obtained by spline smoothing)
listvar matrix of variables which permit to plot bubbles on map using the tk window
listnomvar names of variables listvar
criteria a vector of size n of boolean which permit to represent preselected sites with a cross, using the tcltk window
carte matrix with 2 columns for drawing spatial polygonal contours : x and y coordinates of the vertices of the polygon
label a list of character of size n with names of sites
cex.lab character size of label
pch 16 by default, symbol for selected points
col "blue" by default, colors of points on the angle plot
xlab a title for the graphic x-axis
ylab a title for the graphic y-axis
lablong a title for the map x-axis
lablat a title for the map y-axis
axes a boolean with TRUE for drawing axes on the map

Details

For each couple of sites (s_i,s_j), the graphic represents on the y-axis the absolute difference between var_i and var_j :

D_ij=abs(var_i-var_j)


and on the x-axis the angle theta_ij between vector(s_is_j) and the x-axis. Possibility to represent a smoothing spline regression quantile g_alpha. For 0<alpha<1,

Pr[D_ij<g_alpha(theta_ij)]=alpha

If that case, only the pair of sites (s_i,s_j) verifying :

D_ij>g_max(alpha)(theta_ij)

are represented.

Value

A matrix of boolean of size n x p. TRUE if pair of sites was in the last selection

Author(s)

Thomas-Agnan Christine, Aragon Yves, Ruiz-Gazen Anne, Laurent Thibault, Robidou Lauriane

References

Aragon Yves, Perrin Olivier, Ruiz-Gazen Anne, Thomas-Agnan Christine (2009), Statistique et Econométrie pour données géoréférencées : modèles et études de cas

See Also

variocloudmap,driftmap

Examples

# Data  afcon
data(afcon)

africa <- readShapePoly(system.file("shapes/Africa.shp", package = "GeoXp")[1])
africa.contour<-spdf2list(africa)$poly

obs<-angleplotmap(afcon$x,afcon$y,afcon$totcon,listvar=afcon,
listnomvar=names(afcon),label=afcon$name,cex.lab=0.5,quantiles=c(0.1,0.5,0.95),
criteria=(afcon$totcon>mean(afcon$totcon)),carte=africa.contour)

# Data Meuse
data(meuse)
data(meuse.riv)
obs<-angleplotmap(meuse$x,meuse$y,meuse$copper,
col="green",quantiles=0.9,
listvar=meuse,listnomvar=names(meuse),
xlab="Concentration en plomb (en ppm)",pch=7,carte=meuse.riv[c(21:65,110:153),])

[Package GeoXp version 1.4 Index]