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1. 1. Spatial Statistical Modelling of Insurance Claim Frequency

   University essay from Lunds universitet/Matematisk statistik

   Author : Daniel Faller; [2022]
   Keywords : Insurance risk; claim frequency; Markov chain Monte Carlo MCMC ; Riemann manifold Metropolis adjusted Langevin algorithm MMALA ; spatial statistics; Gaussian Markov random field GMRF ; preconditioned Crank Nicolson Langevin algorithm pCNL ; Gibbs sampling; Bayesian hierarchical modelling; high dimensional; shrinkage prior; horseshoe prior; regularisation.; Mathematics and Statistics;

   Abstract : In this thesis a fully Bayesian hierarchical model that estimates the number of aggregated insurance claims per year for non-life insurances is constructed using Markov chain Monte Carlo based inference with Riemannian Langevin diffusion. Some versions of the model incorporate a spatial effect, viewed as the relative spatial insurance risk that originates from a policyholder's geographical location and where the relative spatial insurance risk is modelled as a continuous spatial field. READ MORE