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Handbook of Big Data Analytics (Springer Handbooks of Computational Statistics) by Wolfgang Karl Härdle; Henry Horng Lu; Xiaotong Shen; Shen Xiaotong is a nonfiction available to read on EtoBox.
What is Handbook of Big Data Analytics (Springer Handbooks of Computational Statistics) about?
A tremendous growth of high-throughput techniques leads to huge data collections that are accumulating in an exponential speed with high volume, velocity, and variety. This creates the challenges of big data analytics for statistical science. These challenges demand creative innovation of statistical methods and smart computational Quantlets, macros, and programs to capture the often genuinely sparse informational content of huge unstructured data. Particularly, the development of analytic methodologies must take into account the co-design of hardware and software to handle the massive data corpus so that the veracity can be achieved and the inherent value can be revealed.This volume of the Handbook of Computational Statistics series collects twentyone chapters to provide advice and guidance to the fast developments of big data analytics. It covers a wide spectrum of methodologies and applications that provide a general overview of this new exciting field of computational statistics. The chapters present topics related to mathematics and statistics for high-dimensional problems, nonlinear structures, sufficient dimension reduction, spatiotemporal dependence, functional data analysi
Who reads Handbook of Big Data Analytics (Springer Handbooks of Computational Statistics)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Wolfgang Karl Härdle; Henry Horng Lu; Xiaotong Shen; Shen Xiaotong
- Publisher
- Springer International Publishing : Imprint: Springer
- Published
- 2018
- Language
- EN
- ISBN
- 9783319182834
- Category
- nonfiction
- Subjects
- Mathematics, Science, Stem
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