plot.varianceMapOut: Plot the standard error map.

In latticeDensity: Density Estimation and Nonparametric Regression on Irregular Regions

Description

Takes as input a varianceMapOut object from the function varianceMap. This plotting function makes a countour plot of the non-parametric regression standard error surface.

Usage

## S3 method for class 'varianceMapOut'
plot(x, ...)

Arguments

x	An object of type varianceMapOut returned by varianceMap.
...	Other arguments to be passed to functions plot, points, lines.

Author(s)

Ronald P. Barry

References

Julie McIntyre, Ronald P. Barry (2018) A Lattice-Based Smoother for Regions with Irregular Boundaries and Holes. Journal of Computational and Graphical Statistics. In Press.

Examples

data(nparExample)
attach(nparExample)
plot.new()
#  Simulate a response variable
index1 <- (grid2[,2]<0.8)|(grid2[,1]>0.6)
Z <- rep(NA,length(grid2[,1]))
n1 <- sum(index1)
n2 <- sum(!index1)
Z[index1] <- 3*grid2[index1,1] + 4 + rnorm(n1,0,sd=0.4)
Z[!index1] <- -2*grid2[!index1,1] + 4 + rnorm(n2,0,sd=0.4)
#
plot(polygon2,type="n")

polygon(polygon2)
points(grid2,pch=19,cex=0.5,xlim=c(-0.1,1))
text(grid2,labels=round(Z,1),pos=4,cex=0.5)
#
nodeFillingOutput <- nodeFilling(poly=polygon2, node_spacing=0.025)
plot(nodeFillingOutput)
formLatticeOutput <- formLattice(nodeFillingOutput)
plot(formLatticeOutput)
hold <- crossvalNparReg(formLatticeOutput,Z,
                       PointPattern=grid2,M=0.5,max_steps = 25)
var_map <- varianceMap(formLatticeOutput,Z,
             PointPattern=grid2,M=0.5,k=hold$k)
plot(var_map)

latticeDensity documentation built on April 18, 2021, 5:06 p.m.