spBayes (version 0.3-9)

FBC07.dat: Synthetic multivariate data with spatial and non-spatial variance structures

Description

The synthetic dataset describes a stationary and isotropic bivariate process. Please refer to the vignette Section 4.2 for specifics.

Usage

data(FBC07.dat)

Format

A data frame of 250 rows and 4 columns. Columns 1 and 2 are coordinates and columns 3 and 4 are response variables.

Source

Finley A.O., S. Banerjee, and B.P. Carlin (2007) spBayes: R package for Univariate and Multivariate Hierarchical Point-referenced Spatial Models. Journal of Statistical Software.

Examples

## Not run: 
# 
# data(FBC07.dat)
# library(geoR)
# 
# max <- 40
# bins <- 20
# pts <- 1:150
# 
# vario.1 <- variog(coords=FBC07.dat[pts,1:2], data=FBC07.dat[pts,3],
#           uvec=(seq(0, max, length=bins)))
# 
# vario.2 <- variog(coords=FBC07.dat[pts,1:2], data=FBC07.dat[pts,4],
#                   uvec=(seq(0,max, length=bins)))
# 
# vario.fit.1 <-variofit(vario.1, ini.cov.pars=c(5.0, 1.0),
#                        cov.model="exponential",
#                        minimisation.function="nls",
#                        weights="equal")
# 
# vario.fit.2 <-variofit(vario.2, ini.cov.pars=c(5.0, 10.0),
#                        cov.model="exponential",
#                        minimisation.function="nls",
#                        weights="equal")
# 
# par(mfrow=c(1,2))
# 
# plot(vario.1$u, vario.1$v, axes=FALSE, type = "n",
#      ylim=c(0,15), xlab="Distance", ylab="Semivariance")
# points(vario.1$u, vario.1$v, pch=19, cex=0.5)
# axis(1, seq(0,max,10))
# axis(2, seq(0,15,5))
# abline(h=vario.fit.1$nugget)
# abline(h=vario.fit.1$cov.pars[1]+vario.fit.1$nugget)
# abline(v=3/(1/vario.fit.1$cov.pars[2]))
# lines(vario.fit.1)
# 
# plot(vario.2$u, vario.2$v, axes=FALSE, type = "n",
#      ylim=c(0,15), xlab="Distance", ylab="")
# points(vario.2$u, vario.2$v, pch=19, cex=0.5)
# axis(1, seq(0,max,10))
# abline(h=vario.fit.2$nugget)
# abline(h=vario.fit.2$cov.pars[1]+vario.fit.2$nugget)
# abline(v=3/(1/vario.fit.2$cov.pars[2]))
# lines(vario.fit.2)
# ## End(Not run)