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Modeling and visualizing hydrologic observations indexed in space and time. This work is heavily indebted to the piece from Wikle, Zammit-Mangion, and Cressie (2019) who are blazing the path to the summit for spatio-temporal statistics

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Space-Time Data Analytics with R

We support the idea that in order to answer the “why” question, Science should address the “where” and “when” questions. Even during the time of early civilization, normadic tribes were known to have used spatio-temporal data to return to seasonal hunting grounds while at a larger scale,datasets on location, weather, geology, plants, animals, and indigenous people were collected by early explorers seeking to map new lands and enrich their kings and queens.

Uncertainty and the role of Statistics

Not only is our world uncertain, our attempts to explain it with Science is also uncertain including the observations we make of it. Statistics is the “Science of Uncertainty,” and it offers a coherent approach to handle this uncertainty.

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Modeling and visualizing hydrologic observations indexed in space and time. This work is heavily indebted to the piece from Wikle, Zammit-Mangion, and Cressie (2019) who are blazing the path to the summit for spatio-temporal statistics

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