geoPlotAllocation: Plot posterior allocation

In bobverity/Rgeoprofile: Geographic profiling in R

Description

Produces plot of posterior allocation from output of MCMC.

Usage

geoPlotAllocation(mcmc, colours = NULL, barBorderCol = NA,
  barBorderWidth = 0.25, mainBorderCol = "black", mainBorderWidth = 2,
  yTicks_on = TRUE, yTicks = seq(0, 1, 0.2), xTicks_on = FALSE,
  xTicks_size = 1, xlab = "", ylab = "posterior allocation",
  mainTitle = "", names = NA, names_size = 1, orderBy = "group")

Arguments

mcmc	stored output obtained by running geoMCMC().
colours	vector of colours for each allocation. If NULL then use default colour scheme.
barBorderCol	colour of borders around each bar. Set as NA to omit this border (useful when there are a large number of observations).
barBorderWidth	line width of borders around each bar.
mainBorderCol	colour of border around plot.
mainBorderWidth	line width of border around plot.
yTicks_on	whether to include ticks on the y-axis.
yTicks	vector of y-axis tick positions.
xTicks_on	whether to include ticks on the x-axis.
xTicks_size	size of ticks on the x-axis.
xlab	x-axis label.
ylab	x-axis label.
mainTitle	main title over plot.
names	individual names of each observation, written horizontally below each bar.
names_size	size of names under each bar.
orderBy	whether to order segments within each bar by "group" or by "probability". If ordered by group, all segments of a particular group are laid down before moving to the next group. If ordered by probability the segments within each bar are ordered from large to small.

Examples

# London example data
d <- LondonExample_crimes
p <- geoParams(data = d, sigma_mean = 1.0, sigma_squared_shape = 2)
m <- geoMCMC(data = d, params = p)
geoPlotAllocation(m)

# John Snow cholera data
d <- Cholera
p <- geoParams(data = d, sigma_mean = 1.0, sigma_squared_shape = 2)
m <- geoMCMC(data = d, params = p, lambda=0.05)
geoPlotAllocation(m, barBorderCol=NA)	# (should allocate all to a single source!)

# simulated data
sim <-rDPM(50, priorMean_longitude = -0.04217491, priorMean_latitude = 
               51.5235505, alpha=1, sigma=1, tau=3)
d <- geoData(sim$longitude, sim $latitude)
p <- geoParams(data = d, sigma_mean = 1.0, sigma_squared_shape = 2)
m <- geoMCMC(data = d, params = p)
geoPlotAllocation(m)

bobverity/Rgeoprofile documentation built on May 12, 2019, 11:28 p.m.