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A zero-inflated mixed-effects spatial point process for grouped storm loss data
The increasing granularity of third-party weather and exposure information can allow insurers to more effectively predict weather-related losses. However, loss outcomes are often reported in spatially grouped observations, such as at the county level, so higher resolution predictors are aggregated t
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