Generate a lurking variable plot of spatial point process residuals against a covariate, for a model fitted to several point patterns.
# S3 method for mppm
lurking(object, covariate, type="eem",
…,
separate = FALSE,
plot.it = TRUE,
covname, oldstyle = FALSE, nx = 512, main="")
The fitted model. An object of class "mppm"
representing a
point process model fitted to several point patterns.
The covariate to be used on the horizontal axis.
Either an expression
which can be evaluated in the
original data, or a list of pixel images, one image for each
point pattern in the original data.
String indicating the type of residuals or weights to be computed.
Choices include "eem"
,
"raw"
, "inverse"
and "pearson"
.
See diagnose.ppm
for all possible choices.
Additional arguments passed to lurking.ppm
,
including arguments controlling the plot.
Logical value indicating whether to compute a separate lurking
variable plot for each of the original point patterns.
If FALSE
(the default), a single lurking-variable plot
is produced by combining residuals from all patterns.
Logical value indicating whether
plots should be shown. If plot.it=FALSE
, only
the computed coordinates for the plots are returned.
See Value.
A string name for the covariate, to be used in axis labels of plots.
Logical flag indicating whether error bounds should be plotted
using the approximation given in the original paper
(oldstyle=TRUE
),
or using the correct asymptotic formula (oldstyle=FALSE
).
Integer. Number of covariate values to be used in the plot.
Character string giving a main title for the plot.
If separate=FALSE
(the default),
the return value is an object
belonging to the class "lurk"
, for which there
are methods for plot
and print
.
See lurking
for details of the format.
If separate=TRUE
, the result is a list of such objects,
and also belongs to the class anylist
so that it can be
printed and plotted.
This function generates a ‘lurking variable’ plot for a
point process model fitted to several point patterns.
Residuals from the model represented by object
are plotted against the covariate specified by covariate
.
This plot can be used to reveal departures from the fitted model.
The function lurking
is generic. This is the method
for the class mppm
.
The argument object
must be a fitted point process model
object of class "mppm"
) produced by the
model-fitting algorithm mppm
.
# NOT RUN {
fit <- mppm(Points ~ Image + Group, demohyper)
lurking(fit, expression(Image), type="P")
lurking(fit, expression(Image), type="P", separate=TRUE)
# }
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