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Computes the case deletion effect measure DFFIT
for a fitted model.
dffit(object, …)# S3 method for ppm
dffit(object, …, collapse = FALSE, dfb = NULL)
A fitted model, such as a point process model
(object of class "ppm").
Additional arguments passed to dfbetas.ppm.
Logical value specifying whether to collapse the vector-valued measure to a scalar-valued measure by adding all the components.
Optional. The result of dfbetas(object),
if it has already been computed.
A measure (object of class "msr").
The case deletion effect measure DFFIT is a model diagnostic
traditionally used for regression models. In that context,
DFFIT[i,j] is the negative change, in the value of the
jth term in the linear predictor, that would occur if the ith
data value was deleted. It is closely related to the
diagnostic DFBETA.
For a spatial point process model, dffit computes
the analogous spatial case deletion diagnostic, described in
Baddeley, Rubak and Turner (2019).
Baddeley, A., Rubak, E. and Turner, R. (2019) Leverage and influence diagnostics for Gibbs spatial point processes. Spatial Statistics 29, 15--48.
# NOT RUN {
# }
# NOT RUN {
X <- rpoispp(function(x,y) { exp(3+3*x) })
fit <- ppm(X ~x+y)
# }
# NOT RUN {
plot(dffit(fit))
plot(dffit(fit, collapse=TRUE))
# }
# NOT RUN {
# }
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