# anova.mppm

0th

Percentile

##### ANOVA for Fitted Multiple Point Process Models

Performs analysis of deviance for two or more fitted multiple point process models.

Keywords
models, methods, spatial
##### Usage
## S3 method for class 'mppm':
anova(object, \dots, test=NULL, override=FALSE)
##### Arguments
object
A fitted multiple point process model (object of class "mppm").
...
One or more fitted multiple point process models.
test
Type of hypothesis test to perform. A character string, partially matching one of "Chisq", "F" or "Cp", or NULL.
override
Logical flag indicating whether to proceed even when there is no statistical theory to support the calculation.
##### Details

This is a method for 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.

##### Value

• An object of class "anova", or NULL.

mppm

• anova.mppm
##### Examples
H <- hyperframe(X=waterstriders)
mod0 <- mppm(X~1, H, Poisson())
modx <- mppm(X~x, H, Poisson())
anova.mppm(mod0, modx, test="Chi")`
Documentation reproduced from package spatstat, version 1.41-1, License: GPL (>= 2)

### Community examples

Looks like there are no examples yet.