Given a fitted Spatial Logistic Regression model, this function computes the fitted probabilities for each pixel, or the fitted probabilities at each original data point.
# S3 method for slrm
fitted(object, ..., type="probabilities",
dataonly=FALSE, leaveoneout=FALSE)
A pixel image (object of class "im"
) containing the
fitted probability for each pixel,
or a numeric vector containing the fitted probability at each data point.
a fitted spatial logistic regression model.
An object of class "slrm"
.
Ignored.
Character string (partially) matching one of
"probabilities"
, "intensity"
or "link"
determining the quantity that should be predicted.
Logical. If TRUE
, then values will only be computed
at the points of the data point pattern. If FALSE
, then
values will be computed at the pixels used to fit the model.
Logical value
specifying whether to perform a leave-one-out calculation
when dataonly=TRUE
. If leaveoneout=TRUE
,
the fitted value at each data point X[i]
is calculated
by re-fitting the model to the data with X[i]
removed.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au and Rolf Turner rolfturner@posteo.net.
This is a method for the generic function
fitted
for spatial logistic regression models
(objects of class "slrm"
, usually obtained
from the function slrm
).
By default, the algorithm computes the fitted probabilities of the presence of a random point in each pixel, and returns them as an image.
If dataonly=TRUE
, the algorithm computes the fitted
presence probabilities only at the locations of the original data points.
slrm
,
fitted
X <- rpoispp(42)
fit <- slrm(X ~ x+y)
plot(fitted(fit))
fitted(fit, dataonly=TRUE)
Run the code above in your browser using DataLab