## S3 method for class 'mppm':
anova(object, \dots, test=NULL, override=FALSE)
"mppm"
)."Chisq"
, "F"
or "Cp"
,
or NULL
."anova"
, or NULL
.anova
for comparing several
fitted multiple point process models (objects of class "mppm"
,
usually generated by the model-fitting function mppm
). If the fitted models are all Poisson point processes,
then this function performs an Analysis of Deviance of
the fitted models. The output shows the deviance differences
(i.e. 2 times log likelihood ratio),
the difference in degrees of freedom, and (if test="Chi"
)
the two-sided p-values for the chi-squared tests. Their interpretation
is very similar to that in anova.glm
.
If some of the fitted models are not Poisson point processes,
then there is no statistical theory available to support
a similar analysis. The function issues a warning,
and (by default) returns a NULL
value.
However if override=TRUE
,
then a kind of analysis of deviance table will be printed.
The `deviance' differences in this table are equal to 2 times the differences
in the maximised values of the log pseudolikelihood (see
mppm
). At the time of writing, there is no statistical
theory to support inferential interpretation of log pseudolikelihood
ratios. The override
option is provided for research purposes
only!
The argument test
determines which hypothesis test, if any, will
be performed to compare the models. The argument test
should be a character string, partially matching one of
"Chisq"
, "F"
or "Cp"
,
or NULL
. The first option "Chisq"
gives
the likelihood ratio test based on the asymptotic chi-squared
distribution of the deviance difference.
The meaning of the other options is explained in
anova.glm
.
For random effects models, only "Chisq"
is
available, and again gives the likelihood ratio test.
mppm
H <- hyperframe(X=waterstriders)
mod0 <- mppm(X~1, H, Poisson())
modx <- mppm(X~x, H, Poisson())
anova.mppm(mod0, modx, test="Chi")
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