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Abstract:
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Datasets observed over space and time have become increasingly important due to its many applications in different fields such as medicine, public health, biological sciences, environmental science and image data. Both spatiotemporal methods and functional data analysis techniques are used to model and analyse these types of data considering the spatial and temporal aspects. In this talk we will present an integral framework for modeling and analysing functional which are spatially correlated. In particular we wish to integrate existing approaches and identify gaps for analyzing a wide variety of spatially correlated functional data and provide the practitioner with objective choices to identify the best method to analyze their data.
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