Pages that link to "Item:Q961716"
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The following pages link to Approximate methods in Bayesian point process spatial models (Q961716):
Displaying 11 items.
- Approximate inference for disease mapping (Q959339) (← links)
- Editorial. Spatial statistics: methods, models \& computation (Q961710) (← links)
- Statistical inference for doubly stochastic multichannel Poisson processes: a PCA approach (Q961932) (← links)
- sppmix: Poisson point process modeling using normal mixture models (Q1729311) (← links)
- A CASE STUDY ON POINT PROCESS MODELLING IN DISEASE MAPPING (Q3598442) (← links)
- Maximum Likelihood Estimation of the Dead Time Period Duration in the Modulated Semi-synchronous Generalized Flow of Events (Q4690223) (← links)
- Hierarchical Bayesian modeling of marked non-homogeneous Poisson processes with finite mixtures and inclusion of covariate information (Q5130552) (← links)
- Quantification of annual wildfire risk; A spatio-temporal point process approach. (Q5148616) (← links)
- Bayesian Wombling for Spatial Point Processes (Q5850974) (← links)
- Approximate Bayesian inference for a spatial point process model exhibiting regularity and random aggregation (Q5872952) (← links)
- A mechanistic spatio‐temporal modeling of COVID‐19 data (Q6149264) (← links)
