Statistical And Computational Methods In Data Analysis

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Data Analysis

Author : Siegmund Brandt
Publisher : Springer Science & Business Media
ISBN 13 : 3319037625
Total Pages : 532 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 532 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.

Computational and Statistical Methods for Analysing Big Data with Applications

Author : Shen Liu
Publisher : Academic Press
ISBN 13 : 0081006519
Total Pages : 208 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 208 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

Computational Methods for Data Analysis

Author : Yeliz Karaca
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110493608
Total Pages : 473 pages
Book Rating : 4.1/5 (14 download)

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Book Synopsis Computational Methods for Data Analysis by : Yeliz Karaca

Download or read book Computational Methods for Data Analysis written by Yeliz Karaca and published by Walter de Gruyter GmbH & Co KG. This book was released on 2018-12-17 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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.

Statistical and Computational Methods in Brain Image Analysis

Author : Moo K. Chung
Publisher : CRC Press
ISBN 13 : 1439836353
Total Pages : 436 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Statistical and Computational Methods in Brain Image Analysis by : Moo K. Chung

Download or read book Statistical and Computational Methods in Brain Image Analysis written by Moo K. Chung and published by CRC Press. This book was released on 2013-07-23 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLAB® and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author’s website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics.

Complex Models and Computational Methods in Statistics

Author : Matteo Grigoletto
Publisher : Springer Science & Business Media
ISBN 13 : 884702871X
Total Pages : 228 pages
Book Rating : 4.8/5 (47 download)

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Book Synopsis Complex Models and Computational Methods in Statistics by : Matteo Grigoletto

Download or read book Complex Models and Computational Methods in Statistics written by Matteo Grigoletto and published by Springer Science & Business Media. This book was released on 2013-01-26 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.

Spatial Analysis Along Networks

Author : Atsuyuki Okabe
Publisher : John Wiley & Sons
ISBN 13 : 1119967767
Total Pages : 252 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Spatial Analysis Along Networks by : Atsuyuki Okabe

Download or read book Spatial Analysis Along Networks written by Atsuyuki Okabe and published by John Wiley & Sons. This book was released on 2012-07-02 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Processes on a Network and Network Voronoi Diagrams, to Network K-function and Point Density Estimation Methods, and the Network Huff Model. The authors also discuss and illustrate the undertaking of the statistical tests described in a Geographical Information System (GIS) environment as well as demonstrating the user-friendly free software package SANET. Spatial Analysis Along Networks: Presents a much-needed practical guide to statistical spatial analysis of events on and alongside a network, in a logical, user-friendly order. Introduces the preliminary methods involved, before detailing the advanced, computational methods, enabling the readers a complete understanding of the advanced topics. Dedicates a separate chapter to each of the major techniques involved. Demonstrates the practicalities of undertaking the tests described in the book, using a GIS. Is supported by a supplementary website, providing readers with a link to the free software package SANET, so they can execute the statistical methods described in the book. Students and researchers studying spatial statistics, spatial analysis, geography, GIS, OR, traffic accident analysis, criminology, retail marketing, facility management and ecology will benefit from this book.

Spatial Analysis with R

Author : Tonny J. Oyana
Publisher : CRC Press
ISBN 13 : 100017347X
Total Pages : 281 pages
Book Rating : 4.0/5 (1 download)

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Book Synopsis Spatial Analysis with R by : Tonny J. Oyana

Download or read book Spatial Analysis with R written by Tonny J. Oyana and published by CRC Press. This book was released on 2020-08-31 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R. The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes. New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data mining This second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.

Statistical Methods for Handling Incomplete Data

Author : Jae Kwang Kim
Publisher : CRC Press
ISBN 13 : 1000466299
Total Pages : 380 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Statistical Methods for Handling Incomplete Data by : Jae Kwang Kim

Download or read book Statistical Methods for Handling Incomplete Data written by Jae Kwang Kim and published by CRC Press. This book was released on 2021-11-19 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. Statistical Methods for Handling Incomplete Data covers the most up-to-date statistical theories and computational methods for analyzing incomplete data. Features Uses the mean score equation as a building block for developing the theory for missing data analysis Provides comprehensive coverage of computational techniques for missing data analysis Presents a rigorous treatment of imputation techniques, including multiple imputation fractional imputation Explores the most recent advances of the propensity score method and estimation techniques for nonignorable missing data Describes a survey sampling application Updated with a new chapter on Data Integration Now includes a chapter on Advanced Topics, including kernel ridge regression imputation and neural network model imputation The book is primarily aimed at researchers and graduate students from statistics, and could be used as a reference by applied researchers with a good quantitative background. It includes many real data examples and simulated examples to help readers understand the methodologies.

Spatial Analysis

Author : Tonny J. Oyana
Publisher : CRC Press
ISBN 13 : 1498707645
Total Pages : 316 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Spatial Analysis by : Tonny J. Oyana

Download or read book Spatial Analysis written by Tonny J. Oyana and published by CRC Press. This book was released on 2015-07-28 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present p

Data-Driven Computational Methods

Author : John Harlim
Publisher : Cambridge University Press
ISBN 13 : 1108472478
Total Pages : 171 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Data-Driven Computational Methods by : John Harlim

Download or read book Data-Driven Computational Methods written by John Harlim and published by Cambridge University Press. This book was released on 2018-07-12 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes computational methods for parametric and nonparametric modeling of stochastic dynamics. Aimed at graduate students, and suitable for self-study.

Computational and Statistical Methods for Protein Quantification by Mass Spectrometry

Author : Ingvar Eidhammer
Publisher : John Wiley & Sons
ISBN 13 : 111849377X
Total Pages : 290 pages
Book Rating : 4.1/5 (184 download)

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Book Synopsis Computational and Statistical Methods for Protein Quantification by Mass Spectrometry by : Ingvar Eidhammer

Download or read book Computational and Statistical Methods for Protein Quantification by Mass Spectrometry written by Ingvar Eidhammer and published by John Wiley & Sons. This book was released on 2012-12-10 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive introduction to data analysis in quantitative proteomics This book provides all the necessary knowledge about mass spectrometry based proteomics methods and computational and statistical approaches to pursue the planning, design and analysis of quantitative proteomics experiments. The author’s carefully constructed approach allows readers to easily make the transition into the field of quantitative proteomics. Through detailed descriptions of wet-lab methods, computational approaches and statistical tools, this book covers the full scope of a quantitative experiment, allowing readers to acquire new knowledge as well as acting as a useful reference work for more advanced readers. Computational and Statistical Methods for Protein Quantification by Mass Spectrometry: Introduces the use of mass spectrometry in protein quantification and how the bioinformatics challenges in this field can be solved using statistical methods and various software programs. Is illustrated by a large number of figures and examples as well as numerous exercises. Provides both clear and rigorous descriptions of methods and approaches. Is thoroughly indexed and cross-referenced, combining the strengths of a text book with the utility of a reference work. Features detailed discussions of both wet-lab approaches and statistical and computational methods. With clear and thorough descriptions of the various methods and approaches, this book is accessible to biologists, informaticians, and statisticians alike and is aimed at readers across the academic spectrum, from advanced undergraduate students to post doctorates entering the field.

Computational Methods for Numerical Analysis with R

Author : James P Howard, II
Publisher : CRC Press
ISBN 13 : 1498723640
Total Pages : 257 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Methods for Numerical Analysis with R by : James P Howard, II

Download or read book Computational Methods for Numerical Analysis with R written by James P Howard, II and published by CRC Press. This book was released on 2017-07-12 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code. Every algorithm described is given with a complete function implementation in R, along with examples to demonstrate the function and its use. Computational Methods for Numerical Analysis with R is intended for those who already know R, but are interested in learning more about how the underlying algorithms work. As such, it is suitable for statisticians, economists, and engineers, and others with a computational and numerical background.

Computational Statistics with R

Author :
Publisher : Elsevier
ISBN 13 : 044463441X
Total Pages : 413 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Computational Statistics with R by :

Download or read book Computational Statistics with R written by and published by Elsevier. This book was released on 2014-11-27 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl. The book is designed so that it can be used right away by novices while appealing to experienced users as well. Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered. - Addresses data examples that can be downloaded directly from the R website - No other source is needed to gain practical experience - Focus on the essentials in graphical outlays

Statistical Data Analysis

Author : Glen Cowan
Publisher : Oxford University Press
ISBN 13 : 0198501560
Total Pages : 218 pages
Book Rating : 4.1/5 (985 download)

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Book Synopsis Statistical Data Analysis by : Glen Cowan

Download or read book Statistical Data Analysis written by Glen Cowan and published by Oxford University Press. This book was released on 1998 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are takenfrom particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques,statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).

Computational Methods and Data Analysis for Metabolomics

Author :
Publisher :
ISBN 13 : 9781071602393
Total Pages : pages
Book Rating : 4.6/5 (23 download)

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Book Synopsis Computational Methods and Data Analysis for Metabolomics by :

Download or read book Computational Methods and Data Analysis for Metabolomics written by and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Data-Driven Modeling & Scientific Computation

Author : Jose Nathan Kutz
Publisher :
ISBN 13 : 0199660336
Total Pages : 657 pages
Book Rating : 4.1/5 (996 download)

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Book Synopsis Data-Driven Modeling & Scientific Computation by : Jose Nathan Kutz

Download or read book Data-Driven Modeling & Scientific Computation written by Jose Nathan Kutz and published by . This book was released on 2013-08-08 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine learning, this book develops techniques that allow for the integration of the dynamics of complex systems and big data. MATLAB is used throughout for mathematical solution strategies.