Mapping predicted probabilities for a binary logit BYM model

[Jingjing]

Hi group members,

I have a binary logit BYM model and want to visualise the spatial distribution of the predicted probabilities. Can I get the probability-scale predictions using:

probability<-summary.fitted.values$'0.5%quant'  

Since there are multiple observations per region, when aggregating these to the region level for mapping, should I use 'median(probability)' or 'mean(probability)'? Bayesian models usually report posterior medians, but would the mean be more appropriate here?

Best,

Jingjing

[Elias T. Krainski]

You can check the books at the following link for this kind of problem:

https://www.paulamoraga.com/book-geospatial/

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