| lurking.mppm | R Documentation |
Generate a lurking variable plot of spatial point process residuals against a covariate, for a model fitted to several point patterns.
## S3 method for class 'mppm'
lurking(object, covariate, type="eem",
...,
separate = FALSE,
plot.it = TRUE,
covname, oldstyle = FALSE, nx = 512, main="")
object |
The fitted model. An object of class |
covariate |
The covariate to be used on the horizontal axis.
Either an |
type |
String indicating the type of residuals or weights to be computed.
Choices include |
... |
Additional arguments passed to |
separate |
Logical value indicating whether to compute a separate lurking
variable plot for each of the original point patterns.
If |
plot.it |
Logical value indicating whether
plots should be shown. If |
covname |
A string name for the covariate, to be used in axis labels of plots. |
oldstyle |
Logical flag indicating whether error bounds should be plotted
using the approximation given in the original paper
( |
nx |
Integer. Number of covariate values to be used in the plot. |
main |
Character string giving a main title for the plot. |
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.
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.
, with thanks to Nicholas Read.
lurking.ppm
fit <- mppm(Points ~ Image + Group, demohyper)
lurking(fit, expression(Image), type="P")
lurking(fit, expression(Image), type="P", separate=TRUE)
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