SPODT (version 0.9-1)

spodtSpatialLines: Boundaries of the spatial classification issued from SPODT

Description

This function creates a SpatialLines object that contains the boundaries of the spatial classification issued from the spodt function.

Usage

spodtSpatialLines(object, data)

Arguments

object

an object of class spodt, usually, a result of a call to spodt.

data

a SpatialPointsDataFrame containing the coordinates and the variables. spodt needs planar coordinates. Geographic coordinates have to be projected. Otherwise, euclidian coordinates can be used.

Value

spodt function.

References

• Gaudart J, Graffeo N, Coulibaly D, Barbet G, Rebaudet S, Dessay N, Doumbo O, Giorgi R. SPODT: An R Package to Perform Spatial Partitioning. Journal of Statistical Software 2015;63(16):1-23. http://www.jstatsoft.org/v63/i16/
• Gaudart J, Poudiougou B, Ranque S, Doumbo O. Oblique decision trees for spatial pattern detection: optimal algorithm and application to malaria risk. BMC Medical Research Methodology 2005;5:22
• Gaudart J, Giorgi R, Poudiougou B, Toure O, Ranque S, Doumbo O, Demongeot J. Detection de clusters spatiaux sans point source predefini: utilisation de cinq methodes et comparaison de leurs resultats. Revue d'Epidemiologie et de Sante Publique 2007;55(4):297-306
• Fichet B, Gaudart J, Giusiano B. Bivariate CART with oblique regression trees. International conference of Data Science and Classification, International Federation of Classification Societies, Ljubljana, Slovenia, July 2006.

See Also

spodt, spodt.tree, test.spodt

Examples

data(dataMALARIA)
#Example : number of malaria episodes per child at each household,
          #from November to December 2009, Bandiagara, Mali.
#Copyright: Pr Ogobara Doumbo, MRTC, Bamako, Mali. email: okd[at]icermali.org
coordinates(dataMALARIA)<-c("x","y")
class(dataMALARIA)
proj4string(dataMALARIA)<-"+proj=longlat +datum=WGS84 +ellps=WGS84"
dataMALARIA<-spTransform(dataMALARIA, CRS("+proj=merc +datum=WGS84 +ellps=WGS84"))

gr<-0.07   #graft parameter
rtw<-0.01 #rtwo.min
parm<-25  #min.parent
childm<-2 #min.child
lmx<-7 

sp<-spodt(dataMALARIA@data[,2]~1, dataMALARIA, weight=TRUE, graft=gr, min.ch=childm,
          min.parent=parm, level.max=lmx, rtwo.min=rtw)

ssp<-spodtSpatialLines(sp,dataMALARIA)
plot(ssp)
points(dataMALARIA,cex=log(dataMALARIA@data$z*10))