CODEWITHSUNDEEP
spatstat
Matt Lewis
Matt Lewis

Reputation: 3

Is there a way to calculate standard errors when using predict.mppm?

I'm using spatstat to run some mppm models and would like to be able to calculate standard errors for the predictions as in predict.ppm. I could use predict.ppm on each point process individually of course, but I'm wondering if this in invalid for any reason or if there is a better way of doing so?

Upvotes: 0

Views: 68

Answers (1)

Adrian Baddeley
Adrian Baddeley

Reputation: 2973

This is not yet implemented as an option in predict.mppm. (It is on our long list of things to do. I will move it closer to the top of the list.)

However, it is available by applying predict.ppm to each element of subfits(model), where model was the original fitted model of class mppm. Something like:

m <- mppm(......)
fits <- subfits(m)
Y <- lapply(fits, predict, se=TRUE)

Just to clarify, fits[[i]] is a point process model, of class ppm, for the data in row i of the data hyperframe, implied by the big model m. The parameter estimates and variance estimates in fits[[i]] are based on information from the entire hyperframe. This is not the same as fitting a separate model of class ppm to the data in each row of the hyperframe and calculating predictions and standard errors for those fits.

Upvotes: 1

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