I have been using lppm (point pattern on a linear network) on spatstat with bunch of covariates and fitting a log-linear model but I couldn't see how to check over-fitting. Is there a quick way to do it?
1 Answers
It depends on what you want.
What tool would you use to check overfitting in (say) a linear model?
To identify whether individual observations may have been over-fitted, you could use influence.lppm (from the spatstat.linnet package).
To identify collinearity in the covariates, currently we do not provide a dedicated function in spatstat, but you could use the following trick. If fit is your fitted model of class lppm, first extract the corresponding GLM using
g <- getglmfit(as.ppm(fit))
Next install the package faraway and use the vif function to calculate the variance inflation factors
library(faraway)
vif(g)
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