Introduction to Regression Models with Spatial and Temporal Correlation

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We begin with an introduction how to add dependency to regression models using frequentist tools. After discussing the limitations of this approach we switch to Bayesian techniques. INLA is used to implement regression models, generalised linear models (GLM) and generalised additive models (GAMs) with spatial, spatial-temporal and temporal dependency. We also discuss zero inflated models.

During the course several case studies are presented, in which the statistical theory is integrated with applied analyses in a clear and understandable manner.

Keywords: Spatial dependency and GLMs. Spatial-temporal data and GAMs. Time series. Zero inflation. INLA. Introduction to Bayesian analysis. Diffuse versus informative priors. Mixed effects models with spatial/temporal dependency.