Data Analysis And Related Applications Volume 1 PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data Analysis And Related Applications Volume 1 PDF full book. Access full book title Data Analysis And Related Applications Volume 1.
Author | : Konstantinos N. Zafeiris |
Publisher | : John Wiley & Sons |
Total Pages | : 484 |
Release | : 2022-08-17 |
Genre | : Computers |
ISBN | : 1394165501 |
Download Data Analysis and Related Applications, Volume 1 Book in PDF, ePub and Kindle
The scientific field of data analysis is constantly expanding due to the rapid growth of the computer industry and the wide applicability of computational and algorithmic techniques, in conjunction with new advances in statistical, stochastic and analytic tools. There is a constant need for new, high-quality publications to cover the recent advances in all fields of science and engineering. This book is a collective work by a number of leading scientists, computer experts, analysts, engineers, mathematicians, probabilists and statisticians who have been working at the forefront of data analysis and related applications. The chapters of this collaborative work represent a cross-section of current concerns, developments and research interests in the above scientific areas. The collected material has been divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with related applications.
Author | : Christos H. Skiadas |
Publisher | : John Wiley & Sons |
Total Pages | : 286 |
Release | : 2019-05-21 |
Genre | : Mathematics |
ISBN | : 1786303825 |
Download Data Analysis and Applications 1 Book in PDF, ePub and Kindle
This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models, and techniques, along with appropriate applications. Volume 1 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into three parts: Part 1 presents clustering and regression cases; Part 2 examines grouping and decomposition, GARCH and threshold models, structural equations, and SME modeling; and Part 3 presents symbolic data analysis, time series and multiple choice models, modeling in demography, and data mining.
Author | : Konstantinos N. Zafeiris |
Publisher | : John Wiley & Sons |
Total Pages | : 484 |
Release | : 2022-11-01 |
Genre | : Computers |
ISBN | : 1786307715 |
Download Data Analysis and Related Applications, Volume 1 Book in PDF, ePub and Kindle
The scientific field of data analysis is constantly expanding due to the rapid growth of the computer industry and the wide applicability of computational and algorithmic techniques, in conjunction with new advances in statistical, stochastic and analytic tools. There is a constant need for new, high-quality publications to cover the recent advances in all fields of science and engineering. This book is a collective work by a number of leading scientists, computer experts, analysts, engineers, mathematicians, probabilists and statisticians who have been working at the forefront of data analysis and related applications. The chapters of this collaborative work represent a cross-section of current concerns, developments and research interests in the above scientific areas. The collected material has been divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with related applications.
Author | : Teresa Kowalczyk |
Publisher | : Springer Science & Business Media |
Total Pages | : 504 |
Release | : 2004-04-16 |
Genre | : Computers |
ISBN | : 9783540211204 |
Download Grade Models and Methods for Data Analysis Book in PDF, ePub and Kindle
This book provides a new grade methodology for intelligent data analysis. It introduces a specific infrastructure of concepts needed to describe data analysis models and methods. This monograph is the only book presently available covering both the theory and application of grade data analysis and therefore aiming both at researchers, students, as well as applied practitioners. The text is richly illustrated through examples and case studies and includes a short introduction to software implementing grade methods, which can be downloaded from the editors.
Author | : Konstantinos N. Zafeiris |
Publisher | : John Wiley & Sons |
Total Pages | : 452 |
Release | : 2022-10-25 |
Genre | : Computers |
ISBN | : 1786307723 |
Download Data Analysis and Related Applications, Volume 2 Book in PDF, ePub and Kindle
The scientific field of data analysis is constantly expanding due to the rapid growth of the computer industry and the wide applicability of computational and algorithmic techniques, in conjunction with new advances in statistical, stochastic and analytic tools. There is a constant need for new, high-quality publications to cover the recent advances in all fields of science and engineering. This book is a collective work by a number of leading scientists, computer experts, analysts, engineers, mathematicians, probabilists and statisticians who have been working at the forefront of data analysis and related applications. The chapters of this collaborative work represent a cross-section of current concerns, developments and research interests in the above scientific areas. The collected material has been divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with related applications.
Author | : Xue-Kun Song |
Publisher | : Springer Science & Business Media |
Total Pages | : 356 |
Release | : 2007-07-27 |
Genre | : Mathematics |
ISBN | : 0387713921 |
Download Correlated Data Analysis: Modeling, Analytics, and Applications Book in PDF, ePub and Kindle
This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.
Author | : S. Ejaz Ahmed |
Publisher | : Springer |
Total Pages | : 390 |
Release | : 2017-03-21 |
Genre | : Mathematics |
ISBN | : 3319415735 |
Download Big and Complex Data Analysis Book in PDF, ePub and Kindle
This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essential new developments in the field. The continued and rapid advancement of modern technology now allows scientists to collect data of increasingly unprecedented size and complexity. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data. Simultaneous variable selection and estimation is one of the key statistical problems involved in analyzing such big and complex data. The purpose of this book is to stimulate research and foster interaction between researchers in the area of high-dimensional data analysis. More concretely, its goals are to: 1) highlight and expand the breadth of existing methods in big data and high-dimensional data analysis and their potential for the advancement of both the mathematical and statistical sciences; 2) identify important directions for future research in the theory of regularization methods, in algorithmic development, and in methodologies for different application areas; and 3) facilitate collaboration between theoretical and subject-specific researchers.
Author | : Krzysztof Jajuga |
Publisher | : Springer Nature |
Total Pages | : 334 |
Release | : 2020-08-28 |
Genre | : Business & Economics |
ISBN | : 3030523489 |
Download Classification and Data Analysis Book in PDF, ePub and Kindle
This volume gathers peer-reviewed contributions on data analysis, classification and related areas presented at the 28th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2019, held in Szczecin, Poland, on September 18–20, 2019. Providing a balance between theoretical and methodological contributions and empirical papers, it covers a broad variety of topics, ranging from multivariate data analysis, classification and regression, symbolic (and other) data analysis, visualization, data mining, and computer methods to composite measures, and numerous applications of data analysis methods in economics, finance and other social sciences. The book is intended for a wide audience, including researchers at universities and research institutions, graduate and doctoral students, practitioners, data scientists and employees in public statistical institutions.
Author | : Christos H. Skiadas |
Publisher | : John Wiley & Sons |
Total Pages | : 286 |
Release | : 2019-03-04 |
Genre | : Mathematics |
ISBN | : 1119597579 |
Download Data Analysis and Applications 1 Book in PDF, ePub and Kindle
This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models, and techniques, along with appropriate applications. Volume 1 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into three parts: Part 1 presents clustering and regression cases; Part 2 examines grouping and decomposition, GARCH and threshold models, structural equations, and SME modeling; and Part 3 presents symbolic data analysis, time series and multiple choice models, modeling in demography, and data mining.
Author | : Vera Pawlowsky-Glahn |
Publisher | : John Wiley & Sons |
Total Pages | : 405 |
Release | : 2011-09-19 |
Genre | : Mathematics |
ISBN | : 0470711353 |
Download Compositional Data Analysis Book in PDF, ePub and Kindle
It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of ``spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science. Key Features: Reflects the state-of-the-art in compositional data analysis. Gives an overview of the historical development of compositional data analysis, as well as basic concepts and procedures. Looks at advances in algebra and calculus on the simplex. Presents applications in different fields of science, including, genomics, ecology, biology, geochemistry, planetology, chemistry and economics. Explores connections to correspondence analysis and the Dirichlet distribution. Presents a summary of three available software packages for compositional data analysis. Supported by an accompanying website featuring R code. Applied scientists working on compositional data analysis in any field of science, both in academia and professionals will benefit from this book, along with graduate students in any field of science working with compositional data.