List,
I have a set of locations in three dimensional space. Each location has a
continously scaled attribute and I would like to shade or color the volume
between these locations using a simple smoother. At the moment, I am simply
using the cloud() function and coloring and sizing the points based on the
value of the attribute, but I would like to think of these locations as
sampling from a continously scaled "latent" attribute. I would like something
simple to use if possible, since what I need it for is simply illustrative.
Although I imagine that shading a volume in 3D isn't very striaght forward!
There is an example below.
#creating data
library(spdep)
library(RColorBrewer)
#sample size
n <- 200
#coordinates
x_coord <- runif(n,0,10)
y_coord <- runif(n,0,10)
z_coord <- runif(n,0,10)
## w matrix and row normalized
w_raw <- matrix(nrow=length(x_coord),ncol=length(x_coord),1)
for(i in 1:length(x_coord)){for(j in 1:length(x_coord))
{w_raw[i,j]<- 1/(sqrt((x_coord[i]-x_coord[j])^2 + (y_coord[i]-y_coord[j])^2 +
(z_coord[i]-z_coord[j])^2 ))^3}}
diag(w_raw) <- rep(0,n)
row_sum <- rep(1,length(x_coord))
for(i in 1:length(x_coord))
{row_sum[i] <- sum(w_raw[i,]) }
w <- matrix(nrow=length(x_coord),ncol=length(x_coord),1)
for(i in 1:length(x_coord)){for(j in 1:length(x_coord))
{w[i,j] <- w_raw[i,j]/row_sum[i]}}
x <- rbinom(n,1,.5)
parms <- c(12.4,0)
w.listw <- mat2listw(w)
e <- rnorm(n,0,1)
p <- .6
y <- parms[1] + parms[2]*x + (solve(diag(n)- p*w))%*%e
sim.data <- as.data.frame(cbind(y,x,x_coord,y_coord,z_coord))
names(sim.data) <- c("y","x","x_coord","y_coord","z_coord")
error.mod <- errorsarlm(y~x,data = sim.data,w.listw)
summary(error.mod)
brks <- quantile(y, probs=seq(0,1,.20),na.rm=TRUE)
cols <- brewer.pal(length(brks)-1, "YlOrRd")
size <- seq(1:length(cols))/3
cloud(z_coord~x_coord*y_coord,col=cols[findInterval(y,brks,all.inside=TRUE)],
pch=8,cex=size[findInterval(y,brks,all.inside=TRUE)])
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