Modelling systematic effects and latent phenomena in point referenced data.

Charlotte Jones-Todd (University of Aukland)

Thursday 22nd October, 2020 16:00-17:00 Zoom


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Meeting ID: 891 0146 6228

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The spatial location and time of events (or objects) is the currency that point process statistics invests to estimate the drivers of the intensity, or rate of occurrence, of those events. Yet, the  assumed processes giving rise to the observed data typically fail to  represent the full complexity of the driving mechanisms. Ignoring  spatial  or temporal dependence between events leads to incorrect inference,  as does assuming the wrong dependency structure. Latent Gaussian models are a flexible class of model that accounts for dependency structures in a hide all ills fashion; the stochastic  structures in these models absorb and amalgamate the underlying, unaccounted for, mechanisms leading to the observed data. In this talk I will introduce this class of model and discuss recent work using latent Gaussian fields to model the fluctuations in the data that cannot otherwise be accounted for.

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