angleplotmap {GeoXp} | R Documentation |
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.
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)
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 |
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.
A matrix of boolean of size n x p. TRUE if pair of sites was in the last selection
Thomas-Agnan Christine, Aragon Yves, Ruiz-Gazen Anne, Laurent Thibault, Robidou Lauriane
Aragon Yves, Perrin Olivier, Ruiz-Gazen Anne, Thomas-Agnan Christine (2009), Statistique et Econométrie pour données géoréférencées : modèles et études de cas
# 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),])