Computational and Statistical Methods for Analysing Big Data with Applications

Book Computational and Statistical Methods for Analysing Big Data with Applications Cover

Download book entitled Computational and Statistical Methods for Analysing Big Data with Applications by Shen Liu and published by Academic Press in PDF, EPUB and Kindle. Read Computational and Statistical Methods for Analysing Big Data with Applications book directly from your devices anywhere anytime. Click Download Book button to get book file. Read some info about this book below.

  • Publisher : Academic Press
  • Release : 20 November 2015
  • ISBN : 9780081006511
  • Page : 206 pages
  • Rating : 5/5 from 4 voters

Computational and Statistical Methods for Analysing Big Data with Applications Book PDF summary

Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data. Advanced computational and statistical methodologies for analysing big data are developed Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable Case studies are discussed to demonstrate the implementation of the developed methods Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation Computing code/programs are provided where appropriate

DOWNLOAD BOOK

Computational and Statistical Methods for Analysing Big Data with Applications

Computational and Statistical Methods for Analysing Big Data with Applications
  • Author : Shen Liu,James Mcgree,Zongyuan Ge,Yang Xie
  • Publisher : Academic Press
  • Release Date : 2015-11-20
  • ISBN : 9780081006511
DOWNLOAD BOOKComputational and Statistical Methods for Analysing Big Data with Applications

Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. Computational and Statistical Methods for Analysing Big Data with Applications starts with an

Data Analytics, Computational Statistics, and Operations Research for Engineers

Data Analytics, Computational Statistics, and Operations Research for Engineers
  • Author : Debabrata Samanta,SK Hafizul Islam,Naveen Chilamkurti,Mohammad Hammoudeh
  • Publisher : CRC Press
  • Release Date : 2022-04-05
  • ISBN : 9781000550429
DOWNLOAD BOOKData Analytics, Computational Statistics, and Operations Research for Engineers

With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival

Data Analysis and Applications 3

Data Analysis and Applications 3
  • Author : Andreas Makrides,Alex Karagrigoriou,Christos H. Skiadas
  • Publisher : John Wiley & Sons
  • Release Date : 2020-05-05
  • ISBN : 9781786305343
DOWNLOAD BOOKData Analysis and Applications 3

Data analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing computer industry and the wide applicability of computational techniques, in conjunction with new advances of analytic tools. This being the case, the need for literature that addresses this is self-evident. New publications are appearing, covering the need for information from all fields of science and engineering, thanks to the universal relevance of data analysis and

Handbook of Big Data Analytics

Handbook of Big Data Analytics
  • Author : Wolfgang Karl Härdle,Henry Horng-Shing Lu,Xiaotong Shen
  • Publisher : Springer
  • Release Date : 2018-07-20
  • ISBN : 9783319182841
DOWNLOAD BOOKHandbook of Big Data Analytics

Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have

Applications in Statistical Computing

Applications in Statistical Computing
  • Author : Nadja Bauer,Katja Ickstadt,Karsten Lübke,Gero Szepannek,Heike Trautmann,Maurizio Vichi
  • Publisher : Springer Nature
  • Release Date : 2019-10-12
  • ISBN : 9783030251475
DOWNLOAD BOOKApplications in Statistical Computing

This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor

Computational Methods for Data Analysis

Computational Methods for Data Analysis
  • Author : Yeliz Karaca,Carlo Cattani
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release Date : 2018-12-17
  • ISBN : 9783110496369
DOWNLOAD BOOKComputational Methods for Data Analysis

This graduate text covers a variety of mathematical and statistical tools for the analysis of big data coming from biology, medicine and economics. Neural networks, Markov chains, tools from statistical physics and wavelet analysis are used to develop efficient computational algorithms, which are then used for the processing of real-life data using Matlab.

Cyber Defense Mechanisms

Cyber Defense Mechanisms
  • Author : Gautam Kumar,Dinesh Kumar Saini,Nguyen Ha Huy Cuong
  • Publisher : CRC Press
  • Release Date : 2020-09-20
  • ISBN : 9781000171921
DOWNLOAD BOOKCyber Defense Mechanisms

This book discusses the evolution of security and privacy issues and brings related technological tools, techniques, and solutions into one single source. The book will take readers on a journey to understanding the security issues and possible solutions involving various threats, attacks, and defense mechanisms, which include IoT, cloud computing, Big Data, lightweight cryptography for blockchain, and data-intensive techniques, and how it can be applied to various applications for general and specific use. Graduate and postgraduate students, researchers, and those

Functional Statistics and Related Fields

Functional Statistics and Related Fields
  • Author : Germán Aneiros,Enea G. Bongiorno,Ricardo Cao,Philippe Vieu
  • Publisher : Springer
  • Release Date : 2017-04-25
  • ISBN : 9783319558462
DOWNLOAD BOOKFunctional Statistics and Related Fields

This volume collects latest methodological and applied contributions on functional, high-dimensional and other complex data, related statistical models and tools as well as on operator-based statistics. It contains selected and refereed contributions presented at the Fourth International Workshop on Functional and Operatorial Statistics (IWFOS 2017) held in A Coruña, Spain, from 15 to 17 June 2017. The series of IWFOS workshops was initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008. Since then, many of the

Research Anthology on Big Data Analytics, Architectures, and Applications

Research Anthology on Big Data Analytics, Architectures, and Applications
  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release Date : 2021-09-24
  • ISBN : 9781668436639
DOWNLOAD BOOKResearch Anthology on Big Data Analytics, Architectures, and Applications

Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics,

Modern Statistical Methods for Health Research

Modern Statistical Methods for Health Research
  • Author : Yichuan Zhao,(Din) Ding-Geng Chen
  • Publisher : Springer
  • Release Date : 2021-10-21
  • ISBN : 3030724360
DOWNLOAD BOOKModern Statistical Methods for Health Research

This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR,

Big Data and Social Science

Big Data and Social Science
  • Author : Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane
  • Publisher : CRC Press
  • Release Date : 2020-11-18
  • ISBN : 9781000208634
DOWNLOAD BOOKBig Data and Social Science

Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify

Frontiers in Massive Data Analysis

Frontiers in Massive Data Analysis
  • Author : National Research Council,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Applied and Theoretical Statistics,Committee on the Analysis of Massive Data
  • Publisher : National Academies Press
  • Release Date : 2013-09-03
  • ISBN : 9780309287814
DOWNLOAD BOOKFrontiers in Massive Data Analysis

Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive

The Behavioral and Social Sciences

The Behavioral and Social Sciences
  • Author : National Research Council,Division of Behavioral and Social Sciences and Education,Commission on Behavioral and Social Sciences and Education,Committee on Basic Research in the Behavioral and Social Sciences
  • Publisher : National Academies Press
  • Release Date : 1988-02-01
  • ISBN : 9780309037495
DOWNLOAD BOOKThe Behavioral and Social Sciences

This volume explores the scientific frontiers and leading edges of research across the fields of anthropology, economics, political science, psychology, sociology, history, business, education, geography, law, and psychiatry, as well as the newer, more specialized areas of artificial intelligence, child development, cognitive science, communications, demography, linguistics, and management and decision science. It includes recommendations concerning new resources, facilities, and programs that may be needed over the next several years to ensure rapid progress and provide a high level of returns

Data Science and Social Research

Data Science and Social Research
  • Author : N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino
  • Publisher : Springer
  • Release Date : 2017-11-17
  • ISBN : 9783319554778
DOWNLOAD BOOKData Science and Social Research

This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the

Big Data Analytics

Big Data Analytics
  • Author : Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao
  • Publisher : Springer
  • Release Date : 2016-10-12
  • ISBN : 9788132236283
DOWNLOAD BOOKBig Data Analytics

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big