Statistics for Spatio-Temporal Data

✍ Noel Cressie, Christopher K. Wikle 📂 Library 📅 2011 🏛 Wiley 🌐 English

A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methodsThis book has been honored with the 2011 PROSE Award in the Mathematics category by the Ameri

Statistical Methods for Spatio-Temporal

📁 Statistical Methods for Spatio-Temporal Systems

✍ Barbel Finkenstadt, Leonhard Held 📂 Library 📅 2006 🏛 Chapman and Hall\/CRC 🌐 English

Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities.Contributed by leading researchers in the f

Spatio-Temporal Data Streams

📁 Spatio-Temporal Data Streams

✍ Zdravko Galić (auth.) 📂 Library 📅 2016 🏛 Springer-Verlag New York 🌐 English

This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all dif

Spatio-Temporal Data Analytics for Wind

📁 Spatio-Temporal Data Analytics for Wind Energy Integration

✍ Lei Yang, Miao He, Junshan Zhang, Vijay Vittal (auth.) 📂 Library 📅 2014 🏛 Springer International Publishing 🌐 English

This SpringerBrief presents spatio-temporal data analytics for wind energy integration using stochastic modeling and optimization methods. It explores techniques for efficiently integrating renewable energy generation into bulk power grids. The operational challenges of wind, and its variability

Spatio-Temporal Statistics With R

📁 Spatio-Temporal Statistics With R

✍ Christopher Wikle; Andrew Zammit Mangion; Noel Cressie 📂 Library 📅 2019 🏛 CRC Press 🌐 English

The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps. Spatio-Temporal Statistics w

Spatio-Temporal Statistics With R

📁 Spatio-Temporal Statistics With R

✍ Christopher Wikle; Andrew Zammit Mangion; Noel Cressie 📂 Library 📅 2019 🏛 CRC Press 🌐 English

The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps. Spatio-Temporal Statistics w