Java JDK 1.2 or higher (for JRI/REngine JDK 1.4 or higher). If it is not already installed, you can get it here.
Sys.setenv("R_REMOTES_NO_ERRORS_FROM_WARNINGS" = "true")
if (!require("devtools"))
install.packages("devtools")
devtools::install_github("jhagenauer/gwann",INSTALL_opts=c("--no-multiarch"))
library(ggplot2)
library(viridis)
library(reshape2)
library(gwann)
data(toy4)
dm<-as.matrix(dist(toy4[,c("lon","lat")]) )
x<-as.matrix(toy4[,c("x1","x2")])
y<-as.numeric(toy4[,c("y")] )
r<-gwann(x=x,y=y,dm=dm,trainIdx=1:nrow(x),predIdx=1:nrow(x),nrHidden=5,batchSize=100,lr=0.01,adaptive=F,gridSearch=T,minBw=1,maxBw=2)
print(paste("RMSE: ",r$rmse))
print(paste("Iterations: ",r$its))
print(paste("Bandwidth: ",r$bw))
# predictions
s<-cbind( Prediction=diag(r$predictions), toy4[,c("lon","lat")] )
ggplot(s,aes(lon,lat,fill=Prediction)) + geom_raster() + scale_fill_viridis() + coord_fixed()
# surfaces
s<-cbind( t(r$weights[[2]]), toy4[,c("lon","lat")] )
colnames(s)<-c(paste("Neuron",1:5),"Bias Neuron","lon","lat")
m<-melt(s,id.vars=c("lon","lat"))
ggplot(m,aes(lon,lat,fill=value)) + geom_raster() + facet_wrap(~variable) + scale_fill_viridis() + coord_fixed()
Hagenauer, Julian, and Marco Helbich. "A geographically weighted artificial neural network." International Journal of Geographical Information Science (2021): 1-21.