diagnose.ppm(object, ..., type="raw", which="all", sigma=NULL,
rbord=reach(object), cumulative=TRUE,
plot.it=TRUE,
plot.neg="image", plot.smooth="imagecontour", plot.sd,
rv = NULL, plot.sd, spacing=0.1,
srange=NULL, monochrome=FALSE)
"ppm"
)
for which diagnostics should be produced. This object
is usually obtained from ppm
."eem"
for the Stoyan-Grabarnik exponential energy weights,
"raw"
for the raw residuals,
"inverse"
for the inverse-lam"all"
, "marks"
, "smooth"
,
"x"
, "y"
and "sum"
.
Multiple choices may be g"smooth"
option.density.ppp
) or the appearance of the plots
(passed to plot.default
).rbord
units away from the edge of the window.cumulative=TRUE
) or the
plots of marginal integrals of the smoothed residual field
(plot.it=FALSE
,
the computed diagnostic quantities are returned without plotting them."discrete"
or "image"
indicating how the density part of the residual measure should be plotted."image"
, "persp"
, "contour"
or "imagecontour"
indicating how the smoothed residual field should be plotted."x"
and "y"
plots. The default is TRUE
for Poisson models and
FALSE
for non-Poisson models. See Details.object
but will instead
be taken directly from this vector."diagppm"
which contains
the coordinates needed to reproduce the selected plots.
This object can be plotted using plot.diagppm
and printed using print.diagppm
.qqplot.ppm
. The argument object
must be a fitted point process model
(object of class "ppm"
) typically produced by the maximum
pseudolikelihood fitting algorithm ppm
).
The argument type
selects the type of residual or weight
that will be computed. Current options are:
[object Object],[object Object]
The argument which
selects the type of plot that is
produced. Options are:
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The argument rbord
ensures there are no edge
effects in the computation of the residuals. The diagnostic calculations
will be confined to those points of the data pattern which are
at least rbord
units away from the edge of the window.
The value of rbord
should be greater than or equal to
the range of interaction permitted in the model.
The argument rv
would normally be used only by experts.
It enables the user to substitute arbitrary values for the
residuals or marks, overriding the usual calculations.
If rv
is present, then instead of calculating the residuals from
the fitted model, the algorithm takes the entries of the vector
rv
to be the values of the residuals or marks,
and plots them in the manner appropriate to the type of residual
or mark selected by type
. The length of rv
must equal
the number of points in the original data point pattern
(if type="eem"
) or the number of quadrature (data and dummy)
points used to fit the model (if type="raw"
,
type="inverse"
or type="pearson"
).
The return value is an object of class "diagppm"
.
There are methods for plot
and print
for such objects.
See the Examples.
See also the companion functions qqplot.ppm
, which produces a
Q-Q plot of the residuals, and lurking
, which produces
lurking variable plots for any spatial covariate.
Stoyan, D. and Grabarnik, P. (1991) Second-order characteristics for stochastic structures connected with Gibbs point processes. Mathematische Nachrichten, 151:95--100.
residuals.ppm
,
eem
,
ppm.object
,
qqplot.ppm
,
lurking
,
ppm
data(cells)
fit <- ppm(cells, ~x, Strauss(r=0.15), rbord=0.15)
diagnose.ppm(fit, rbord=0.15)
diagnose.ppm(fit, type="pearson", rbord=0.15)
diagnose.ppm(fit, rbord=0.15, which="marks")
diagnose.ppm(fit, rbord=0.15, type="raw", plot.neg="discrete")
# save the diagnostics and plot them later
u <- diagnose.ppm(fit, rbord=0.15, plot.it=FALSE)
plot(u)
plot(u, which="marks")
Run the code above in your browser using DataLab