Computational Statistics In Data Science

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Computational Statistics in Data Science

Author : Richard A. Levine
Publisher : John Wiley & Sons
ISBN 13 : 1119561086
Total Pages : 672 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Computational Statistics in Data Science by : Richard A. Levine

Download or read book Computational Statistics in Data Science written by Richard A. Levine and published by John Wiley & Sons. This book was released on 2022-03-23 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ein unverzichtbarer Leitfaden bei der Anwendung computergestützter Statistik in der modernen Datenwissenschaft In Computational Statistics in Data Science präsentiert ein Team aus bekannten Mathematikern und Statistikern eine fundierte Zusammenstellung von Konzepten, Theorien, Techniken und Praktiken der computergestützten Statistik für ein Publikum, das auf der Suche nach einem einzigen, umfassenden Referenzwerk für Statistik in der modernen Datenwissenschaft ist. Das Buch enthält etliche Kapitel zu den wesentlichen konkreten Bereichen der computergestützten Statistik, in denen modernste Techniken zeitgemäß und verständlich dargestellt werden. Darüber hinaus bietet Computational Statistics in Data Science einen kostenlosen Zugang zu den fertigen Einträgen im Online-Nachschlagewerk Wiley StatsRef: Statistics Reference Online. Außerdem erhalten die Leserinnen und Leser: * Eine gründliche Einführung in die computergestützte Statistik mit relevanten und verständlichen Informationen für Anwender und Forscher in verschiedenen datenintensiven Bereichen * Umfassende Erläuterungen zu aktuellen Themen in der Statistik, darunter Big Data, Datenstromverarbeitung, quantitative Visualisierung und Deep Learning Das Werk eignet sich perfekt für Forscher und Wissenschaftler sämtlicher Fachbereiche, die Techniken der computergestützten Statistik auf einem gehobenen oder fortgeschrittenen Niveau anwenden müssen. Zudem gehört Computational Statistics in Data Science in das Bücherregal von Wissenschaftlern, die sich mit der Erforschung und Entwicklung von Techniken der computergestützten Statistik und statistischen Grafiken beschäftigen.

Computational Statistics

Author : Geof H. Givens
Publisher : John Wiley & Sons
ISBN 13 : 1118555481
Total Pages : 496 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Computational Statistics by : Geof H. Givens

Download or read book Computational Statistics written by Geof H. Givens and published by John Wiley & Sons. This book was released on 2012-10-09 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the field: Optimization Integration and Simulation Bootstrapping Density Estimation and Smoothing Within these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods. The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data. The book website now includes comprehensive R code for the entire book. There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.

Elements of Computational Statistics

Author : James E. Gentle
Publisher : Springer Science & Business Media
ISBN 13 : 0387216111
Total Pages : 420 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Elements of Computational Statistics by : James E. Gentle

Download or read book Elements of Computational Statistics written by James E. Gentle and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books

Handbook of Computational Statistics

Author : James E. Gentle
Publisher : Springer
ISBN 13 : 9783662517659
Total Pages : 0 pages
Book Rating : 4.5/5 (176 download)

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Book Synopsis Handbook of Computational Statistics by : James E. Gentle

Download or read book Handbook of Computational Statistics written by James E. Gentle and published by Springer. This book was released on 2017-05-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Computational Statistics - Concepts and Methods (second edition) is a revision of the first edition published in 2004, and contains additional comments and updated information on the existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. This new edition is divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2 - 15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment are discussed. The third part (Chs. 16 - 33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34 - 38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-world applications.

Computational Statistics Handbook with MATLAB

Author : Wendy L. Martinez
Publisher : CRC Press
ISBN 13 : 1420035630
Total Pages : 611 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Computational Statistics Handbook with MATLAB by : Wendy L. Martinez

Download or read book Computational Statistics Handbook with MATLAB written by Wendy L. Martinez and published by CRC Press. This book was released on 2001-09-26 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Approaching computational statistics through its theoretical aspects can be daunting. Often intimidated or distracted by the theory, researchers and students can lose sight of the actual goals and applications of the subject. What they need are its key concepts, an understanding of its methods, experience with its implementation, and practice with

Computational Statistics Handbook with MATLAB

Author : Wendy L. Martinez
Publisher : CRC Press
ISBN 13 : 1420010867
Total Pages : 792 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Computational Statistics Handbook with MATLAB by : Wendy L. Martinez

Download or read book Computational Statistics Handbook with MATLAB written by Wendy L. Martinez and published by CRC Press. This book was released on 2007-12-20 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: As with the bestselling first edition, Computational Statistics Handbook with MATLAB, Second Edition covers some of the most commonly used contemporary techniques in computational statistics. With a strong, practical focus on implementing the methods, the authors include algorithmic descriptions of the procedures as well as

Applications in Statistical Computing

Author : Nadja Bauer
Publisher : Springer Nature
ISBN 13 : 3030251470
Total Pages : 336 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Applications in Statistical Computing by : Nadja Bauer

Download or read book Applications in Statistical Computing written by Nadja Bauer and published by Springer Nature. This book was released on 2019-10-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.

Data Analytics, Computational Statistics, and Operations Research for Engineers

Author : Debabrata Samanta
Publisher : CRC Press
ISBN 13 : 9781003152392
Total Pages : 246 pages
Book Rating : 4.1/5 (523 download)

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Book Synopsis Data Analytics, Computational Statistics, and Operations Research for Engineers by : Debabrata Samanta

Download or read book Data Analytics, Computational Statistics, and Operations Research for Engineers written by Debabrata Samanta and published by CRC Press. This book was released on 2022 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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 analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning"--

Computational and Statistical Methods for Analysing Big Data with Applications

Author : Shen Liu
Publisher : Academic Press
ISBN 13 : 0081006519
Total Pages : 206 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Computational and Statistical Methods for Analysing Big Data with Applications by : Shen Liu

Download or read book Computational and Statistical Methods for Analysing Big Data with Applications written by Shen Liu and published by Academic Press. This book was released on 2015-11-20 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Methodologies and Applications of Computational Statistics for Machine Intelligence

Author : Debabrata Samanta
Publisher : Engineering Science Reference
ISBN 13 : 9781799877028
Total Pages : pages
Book Rating : 4.8/5 (77 download)

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Book Synopsis Methodologies and Applications of Computational Statistics for Machine Intelligence by : Debabrata Samanta

Download or read book Methodologies and Applications of Computational Statistics for Machine Intelligence written by Debabrata Samanta and published by Engineering Science Reference. This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book delves into computational statistics that focus on devising an efficient methodology to obtain quantitative solutions for problems that are devised quantitatively and brings together computational capability and statistical advanced thought processes to solve some of the problems encountered in the field"--

A Computational Approach to Statistical Learning

Author : Taylor Arnold
Publisher : CRC Press
ISBN 13 : 1351694758
Total Pages : 370 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis A Computational Approach to Statistical Learning by : Taylor Arnold

Download or read book A Computational Approach to Statistical Learning written by Taylor Arnold and published by CRC Press. This book was released on 2019-01-23 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods. The text contains annotated code to over 80 original reference functions. These functions provide minimal working implementations of common statistical learning algorithms. Every chapter concludes with a fully worked out application that illustrates predictive modeling tasks using a real-world dataset. The text begins with a detailed analysis of linear models and ordinary least squares. Subsequent chapters explore extensions such as ridge regression, generalized linear models, and additive models. The second half focuses on the use of general-purpose algorithms for convex optimization and their application to tasks in statistical learning. Models covered include the elastic net, dense neural networks, convolutional neural networks (CNNs), and spectral clustering. A unifying theme throughout the text is the use of optimization theory in the description of predictive models, with a particular focus on the singular value decomposition (SVD). Through this theme, the computational approach motivates and clarifies the relationships between various predictive models. Taylor Arnold is an assistant professor of statistics at the University of Richmond. His work at the intersection of computer vision, natural language processing, and digital humanities has been supported by multiple grants from the National Endowment for the Humanities (NEH) and the American Council of Learned Societies (ACLS). His first book, Humanities Data in R, was published in 2015. Michael Kane is an assistant professor of biostatistics at Yale University. He is the recipient of grants from the National Institutes of Health (NIH), DARPA, and the Bill and Melinda Gates Foundation. His R package bigmemory won the Chamber's prize for statistical software in 2010. Bryan Lewis is an applied mathematician and author of many popular R packages, including irlba, doRedis, and threejs.

Data Analysis

Author : Siegmund Brandt
Publisher : Springer Science & Business Media
ISBN 13 : 3319037625
Total Pages : 523 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Data Analysis by : Siegmund Brandt

Download or read book Data Analysis written by Siegmund Brandt and published by Springer Science & Business Media. This book was released on 2014-02-14 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data in laboratory courses, in working for bachelor or master degrees, in thesis work, and in research and professional work.

Applied Statistics and Data Science

Author : Yogendra P. Chaubey
Publisher : Springer Nature
ISBN 13 : 3030861333
Total Pages : 166 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Applied Statistics and Data Science by : Yogendra P. Chaubey

Download or read book Applied Statistics and Data Science written by Yogendra P. Chaubey and published by Springer Nature. This book was released on 2022-01-01 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021. Papers are contributed from established and emerging scholars, covering cutting-edge and contemporary innovative techniques in statistics and data science. Major areas of contribution include Bayesian statistics; computational statistics; data science; semi-parametric regression; and stochastic methods in biology, crop science, ecology and engineering. It will be a valuable edited collection for graduate students, researchers, and practitioners in a wide array of applied statistical and data science methods.

Data Analytics, Computational Statistics, and Operations Research for Engineers

Author : Debabrata Samanta
Publisher : CRC Press
ISBN 13 : 1000550427
Total Pages : 296 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Data Analytics, Computational Statistics, and Operations Research for Engineers by : Debabrata Samanta

Download or read book Data Analytics, Computational Statistics, and Operations Research for Engineers written by Debabrata Samanta and published by CRC Press. This book was released on 2022-04-05 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

Statistics with Julia

Author : Yoni Nazarathy
Publisher : Springer Nature
ISBN 13 : 3030709019
Total Pages : 527 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Statistics with Julia by : Yoni Nazarathy

Download or read book Statistics with Julia written by Yoni Nazarathy and published by Springer Nature. This book was released on 2021-09-04 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, distributions, statistical inference, regression analysis, machine learning methods, and the use of Monte Carlo simulation for dynamic stochastic models. Ultimately this text introduces the Julia programming language as a computational tool, uniquely addressing end-users rather than developers. It makes heavy use of over 200 code examples to illustrate dozens of key statistical concepts. The Julia code, written in a simple format with parameters that can be easily modified, is also available for download from the book’s associated GitHub repository online. See what co-creators of the Julia language are saying about the book: Professor Alan Edelman, MIT: With “Statistics with Julia”, Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference. Dr. Viral Shah, CEO of Julia Computing: Yoni and Hayden provide a modern way to learn statistics with the Julia programming language. This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia.

Computational Statistics

Author : James E. Gentle
Publisher : Springer Science & Business Media
ISBN 13 : 0387981446
Total Pages : 732 pages
Book Rating : 4.3/5 (879 download)

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Book Synopsis Computational Statistics by : James E. Gentle

Download or read book Computational Statistics written by James E. Gentle and published by Springer Science & Business Media. This book was released on 2009-07-28 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.

Machine Learning for Signal Processing

Author : Max A. Little
Publisher : Oxford University Press, USA
ISBN 13 : 0198714939
Total Pages : 378 pages
Book Rating : 4.1/5 (987 download)

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Book Synopsis Machine Learning for Signal Processing by : Max A. Little

Download or read book Machine Learning for Signal Processing written by Max A. Little and published by Oxford University Press, USA. This book was released on 2019 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.