Plot Result of Berman Test
Plot the result of Berman's test of goodness-of-fit
## S3 method for class 'bermantest'
plot(x, ...,
lwd=par("lwd"), col=par("col"), lty=par("lty"),
lwd0=lwd, col0=2, lty0=2)x |
Object to be plotted. An object of class |
... |
extra arguments that will be passed to the plotting function
|
col,lwd,lty |
The width, colour and type of lines used to plot the empirical distribution curve. |
col0,lwd0,lty0 |
The width, colour and type of lines used to plot the predicted (null) distribution curve. |
This is the plot method for the class "bermantest".
An object of this class represents the outcome of Berman's test
of goodness-of-fit of a spatial Poisson point process model,
computed by berman.test.
For the Z1 test (i.e. if x was computed using
berman.test( ,which="Z1")),
the plot displays the two cumulative distribution functions
that are compared by the test: namely the empirical cumulative distribution
function of the covariate at the data points, Fhat,
and the predicted
cumulative distribution function of the covariate under the model,
F0, both plotted against the value of the covariate.
Two vertical lines show the mean values of these two distributions.
If the model is correct, the two curves should be close; the test is
based on comparing the two vertical lines.
For the Z2 test (i.e. if x was computed using
berman.test( ,which="Z2")), the plot displays the empirical
cumulative distribution function of the values
U[i] = F0(Y[i]) where Y[i] is the
value of the covariate at the i-th data point. The diagonal line
with equation y=x is also shown. Two vertical lines show the
mean of the values U[i] and the value 1/2. If the
model is correct, the two curves should be close. The test is based on
comparing the two vertical lines.
NULL.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
, Rolf Turner r.turner@auckland.ac.nz
and Ege Rubak rubak@math.aau.dk
# synthetic data: nonuniform Poisson process
X <- rpoispp(function(x,y) { 100 * exp(-x) }, win=square(1))
# fit uniform Poisson process
fit0 <- ppm(X, ~1)
# test covariate = x coordinate
xcoord <- function(x,y) { x }
# test wrong model
k <- berman.test(fit0, xcoord, "Z1")
# plot result of test
plot(k, col="red", col0="green")
# Z2 test
k2 <- berman.test(fit0, xcoord, "Z2")
plot(k2, col="red", col0="green")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.