Astrostatistics And Data Mining

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Astrostatistics and Data Mining

Luis Manuel Sarro,Laurent Eyer,William O'Mullane,Joris De Ridder
Astrostatistics and Data Mining Book PDF

Author : Luis Manuel Sarro,Laurent Eyer,William O'Mullane,Joris De Ridder
Publisher : Springer Science & Business Media
Page : 259 pages
File Size : 42,7 Mb
Release : 2012-08-04
Category : Science
ISBN : 9781461433231

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Astrostatistics and Data Mining by Luis Manuel Sarro,Laurent Eyer,William O'Mullane,Joris De Ridder Pdf

​​​​​ ​This volume provides an overview of the field of Astrostatistics understood as the sub-discipline dedicated to the statistical analysis of astronomical data. It presents examples of the application of the various methodologies now available to current open issues in astronomical research. The technical aspects related to the scientific analysis of the upcoming petabyte-scale databases are emphasized given the importance that scalable Knowledge Discovery techniques will have for the full exploitation of these databases. Based on the 2011 Astrostatistics and Data Mining in Large Astronomical Databases conference and school, this volume gathers examples of the work by leading authors in the areas of Astrophysics and Statistics, including a significant contribution from the various teams that prepared for the processing and analysis of the Gaia data.

Statistics, Data Mining, and Machine Learning in Astronomy

Željko Ivezić,Andrew J. Connolly,Jacob T. VanderPlas,Alexander Gray
Statistics Data Mining and Machine Learning in Astronomy Book PDF

Author : Željko Ivezić,Andrew J. Connolly,Jacob T. VanderPlas,Alexander Gray
Publisher : Princeton University Press
Page : 550 pages
File Size : 46,9 Mb
Release : 2014-01-12
Category : Science
ISBN : 9780691151687

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Statistics, Data Mining, and Machine Learning in Astronomy by Željko Ivezić,Andrew J. Connolly,Jacob T. VanderPlas,Alexander Gray Pdf

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from contemporary astronomical surveys Uses a freely available Python codebase throughout Ideal for students and working astronomers

Statistical Methods for Astronomical Data Analysis

Asis Kumar Chattopadhyay,Tanuka Chattopadhyay
Statistical Methods for Astronomical Data Analysis Book PDF

Author : Asis Kumar Chattopadhyay,Tanuka Chattopadhyay
Publisher : Springer
Page : 349 pages
File Size : 53,5 Mb
Release : 2014-10-01
Category : Mathematics
ISBN : 9781493915071

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Statistical Methods for Astronomical Data Analysis by Asis Kumar Chattopadhyay,Tanuka Chattopadhyay Pdf

This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for astronomical problems, including regression techniques, along with their usefulness for data set problems related to size and dimension. Analysis of missing data is an important part of the book because of its significance for work with astronomical data. Both existing and new techniques related to dimension reduction and clustering are illustrated through examples. There is detailed coverage of applications useful for classification, discrimination, data mining and time series analysis. Later chapters explain simulation techniques useful for the development of physical models where it is difficult or impossible to collect data. Finally, coverage of the many R programs for techniques discussed makes this book a fantastic practical reference. Readers may apply what they learn directly to their data sets in addition to the data sets included by the authors.

Advances in Machine Learning and Data Mining for Astronomy

Michael J. Way,Jeffrey D. Scargle,Kamal M. Ali,Ashok N. Srivastava
Advances in Machine Learning and Data Mining for Astronomy Book PDF

Author : Michael J. Way,Jeffrey D. Scargle,Kamal M. Ali,Ashok N. Srivastava
Publisher : CRC Press
Page : 744 pages
File Size : 43,8 Mb
Release : 2012-03-29
Category : Computers
ISBN : 9781439841747

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Advances in Machine Learning and Data Mining for Astronomy by Michael J. Way,Jeffrey D. Scargle,Kamal M. Ali,Ashok N. Srivastava Pdf

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines

Statistics, Data Mining, and Machine Learning in Astronomy

Željko Ivezić,Andrew J. Connolly,Jacob T. VanderPlas,Alexander Gray
Statistics Data Mining and Machine Learning in Astronomy Book PDF

Author : Željko Ivezić,Andrew J. Connolly,Jacob T. VanderPlas,Alexander Gray
Publisher : Princeton University Press
Page : 548 pages
File Size : 50,7 Mb
Release : 2019-12-03
Category : Computers
ISBN : 9780691198309

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Statistics, Data Mining, and Machine Learning in Astronomy by Željko Ivezić,Andrew J. Connolly,Jacob T. VanderPlas,Alexander Gray Pdf

"As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. The updates in this new edition will include fixing "code rot," correcting errata, and adding some new sections. In particular, the new sections include new material on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest"--

Modern Statistical Methods for Astronomy

Eric D. Feigelson,G. Jogesh Babu
Modern Statistical Methods for Astronomy Book PDF

Author : Eric D. Feigelson,G. Jogesh Babu
Publisher : Cambridge University Press
Page : 495 pages
File Size : 44,7 Mb
Release : 2012-07-12
Category : Science
ISBN : 9780521767279

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Modern Statistical Methods for Astronomy by Eric D. Feigelson,G. Jogesh Babu Pdf

Modern Statistical Methods for Astronomy: With R Applications.

Astrostatistics

Gutti Jogesh Babu,E.D. Feigelson
Astrostatistics Book PDF

Author : Gutti Jogesh Babu,E.D. Feigelson
Publisher : CRC Press
Page : 242 pages
File Size : 43,7 Mb
Release : 1996-08-01
Category : Mathematics
ISBN : 0412983915

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Astrostatistics by Gutti Jogesh Babu,E.D. Feigelson Pdf

Modern astronomers encounter a vast range of challenging statistical problems, yet few are familiar with the wealth of techniques developed by statisticians. Conversely, few statisticians deal with the compelling problems confronted in astronomy. Astrostatistics bridges this gap. Authored by a statistician-astronomer team, it provides professionals and advanced students in both fields with exposure to issues of mutual interest. In the first half of the book the authors introduce statisticians to stellar, galactic, and cosmological astronomy and discuss the complex character of astronomical data. For astronomers, they introduce the statistical principles of nonparametrics, multivariate analysis, time series analysis, density estimation, and resampling methods. The second half of the book is organized by statistical topic. Each chapter contains examples of problems encountered astronomical research and highlights methodological issues. The final chapter explores some controversial issues in astronomy that have a strong statistical component. The authors provide an extensive bibliography and references to software for implementing statistical methods. The "marriage" of astronomy and statistics is a natural one and benefits both disciplines. Astronomers need the tools and methods of statistics to interpret the vast amount of data they generate, and the issues related to astronomical data pose intriguing challenges for statisticians. Astrostatistics paves the way to improved statistical analysis of astronomical data and provides a common ground for future collaboration between the two fields.

Data Science Thinking

Longbing Cao
Data Science Thinking Book PDF

Author : Longbing Cao
Publisher : Springer
Page : 390 pages
File Size : 53,9 Mb
Release : 2018-08-17
Category : Computers
ISBN : 9783319950921

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Data Science Thinking by Longbing Cao Pdf

This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.

Statistics, Data Mining, and Machine Learning in Astronomy

Željko Ivezić,Andrew Connolly,Jacob VanderPlas,Alexander Gray
Statistics Data Mining and Machine Learning in Astronomy Book PDF

Author : Željko Ivezić,Andrew Connolly,Jacob VanderPlas,Alexander Gray
Publisher : Unknown
Page : 552 pages
File Size : 53,5 Mb
Release : 2014
Category : Electronic
ISBN : OCLC:1107417483

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Statistics, Data Mining, and Machine Learning in Astronomy by Željko Ivezić,Andrew Connolly,Jacob VanderPlas,Alexander Gray Pdf

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from contemporary astronomical surveys Uses a freely available Python codebase throughout Ideal for students and working astronomers.

Astrostatistical Challenges for the New Astronomy

Joseph M. Hilbe
Astrostatistical Challenges for the New Astronomy Book PDF

Author : Joseph M. Hilbe
Publisher : Springer Science & Business Media
Page : 247 pages
File Size : 46,6 Mb
Release : 2012-11-07
Category : Mathematics
ISBN : 9781461435082

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Astrostatistical Challenges for the New Astronomy by Joseph M. Hilbe Pdf

Astrostatistical Challenges for the New Astronomy presents a collection of monographs authored by several of the disciplines leading astrostatisticians, i.e. by researchers from the fields of statistics and astronomy-astrophysics, who work in the statistical analysis of astronomical and cosmological data. Eight of the ten monographs are enhancements of presentations given by the authors as invited or special topics in astrostatistics papers at the ISI World Statistics Congress (2011, Dublin, Ireland). The opening chapter, by the editor, was adapted from an invited seminar given at Los Alamos National Laboratory (2011) on the history and current state of the discipline; the second chapter by Thomas Loredo was adapted from his invited presentation at the Statistical Challenges in Modern Astronomy V conference (2011, Pennsylvania State University), presenting insights regarding frequentist and Bayesian methods of estimation in astrostatistical analysis. The remaining monographs are research papers discussing various topics in astrostatistics. The monographs provide the reader with an excellent overview of the current state astrostatistical research, and offer guidelines as to subjects of future research. Lead authors for each chapter respectively include Joseph M. Hilbe (Jet Propulsion Laboratory and Arizona State Univ); Thomas J. Loredo (Dept of Astronomy, Cornell Univ); Stefano Andreon (INAF-Osservatorio Astronomico di Brera, Italy); Martin Kunz ( Institute for Theoretical Physics, Univ of Geneva, Switz); Benjamin Wandel ( Institut d'Astrophysique de Paris, Univ Pierre et Marie Curie, France); Roberto Trotta (Astrophysics Group, Dept of Physics, Imperial College London, UK); Phillip Gregory (Dept of Astronomy, Univ of British Columbia, Canada); Marc Henrion (Dept of Mathematics, Imperial College, London, UK); Asis Kumar Chattopadhyay (Dept of Statistics, Univ of Calcutta, India); Marisa March (Astrophysics Group, Dept of Physics, Imperial College, London, UK)./body

Highlights of Spanish Astrophysics V

Jose M. Diego,LuisJ. Goicoechea,J. Ignacio González-Serrano,Javier Gorgas
Highlights of Spanish Astrophysics V Book PDF

Author : Jose M. Diego,LuisJ. Goicoechea,J. Ignacio González-Serrano,Javier Gorgas
Publisher : Springer Science & Business Media
Page : 566 pages
File Size : 45,5 Mb
Release : 2010-03-18
Category : Science
ISBN : 9783642112508

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Highlights of Spanish Astrophysics V by Jose M. Diego,LuisJ. Goicoechea,J. Ignacio González-Serrano,Javier Gorgas Pdf

Astronomy is a scienti?c discipline that has developed a rapid and impressive growth in Spain. Thirty years ago, Spain occupied a purely anecdotal presence in the international context, but today it occupies the eighth position in the world in publication of astronomical articles, and, among other successes, owns and op- ates ninety per cent of the world’s largest optical telescope GTC (Gran Telescopio Canarias). The Eighth Scienti?c Meeting of the Spanish Astronomical Society (Sociedad Espanol ̃ a de Astronom ́ a, SEA), held in Santander in July 7–11 2008, whose p- ceedings are in your hands, clearly shows the enthusiasm, motivation and quality of the present Spanish astronomical community. The event brought together 322 participants, who represent almost 50% of Spanish professional astronomers. This percentage, together with the continuously increasing, with respect to previous SEA meetings, number of oral presentations and poster contributions (179 and 127 respectively), con?rms that the SEA conferences have become a point of reference to assess the interests and achievements of astrophysical research in Spain. The most important and current topics of modern Astrophysics were taken into accountat thepreliminarymeeting,aswell as the numberandqualityofparticipants and their contributions, to select the invited speakers and oral contributors. We took a week to enjoy the high quality contributions submitted by Spanish astronomers to the Scienti?c Organizing Committee. The selection was dif?cult. We wish to acknowledge the gentle advice and commitment of the SOC members.

Statistics and Data Analysis for Financial Engineering

David Ruppert,David S. Matteson
Statistics and Data Analysis for Financial Engineering Book PDF

Author : David Ruppert,David S. Matteson
Publisher : Springer
Page : 719 pages
File Size : 52,6 Mb
Release : 2015-04-21
Category : Business & Economics
ISBN : 9781493926145

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Statistics and Data Analysis for Financial Engineering by David Ruppert,David S. Matteson Pdf

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

Big Data in Astronomy

Linghe Kong,Tian Huang,Yongxin Zhu,Shenghua Yu
Big Data in Astronomy Book PDF

Author : Linghe Kong,Tian Huang,Yongxin Zhu,Shenghua Yu
Publisher : Elsevier
Page : 440 pages
File Size : 55,5 Mb
Release : 2020-06-13
Category : Science
ISBN : 9780128190852

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Big Data in Astronomy by Linghe Kong,Tian Huang,Yongxin Zhu,Shenghua Yu Pdf

Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world’s largest radio telescope that generates over an Exabyte of data every day, the book offers solutions for coping with the challenges and opportunities presented by the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy. Bridges the gap between radio astronomy and computer science Includes coverage of the observation lifecycle as well as data collection, processing and analysis Presents state-of-the-art research and techniques in big data related to radio astronomy Utilizes real-world examples, such as Square Kilometer Array (SKA) and Five-hundred-meter Aperture Spherical radio Telescope (FAST)

Big Data in Complex Systems

Aboul Ella Hassanien,Ahmad Taher Azar,Vaclav Snasael,Janusz Kacprzyk,Jemal H. Abawajy
Big Data in Complex Systems Book PDF

Author : Aboul Ella Hassanien,Ahmad Taher Azar,Vaclav Snasael,Janusz Kacprzyk,Jemal H. Abawajy
Publisher : Springer
Page : 502 pages
File Size : 46,6 Mb
Release : 2015-01-02
Category : Technology & Engineering
ISBN : 9783319110561

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Big Data in Complex Systems by Aboul Ella Hassanien,Ahmad Taher Azar,Vaclav Snasael,Janusz Kacprzyk,Jemal H. Abawajy Pdf

This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.

Astronomical Image and Data Analysis

J.-L. Starck,F. Murtagh
Astronomical Image and Data Analysis Book PDF

Author : J.-L. Starck,F. Murtagh
Publisher : Springer Science & Business Media
Page : 338 pages
File Size : 55,8 Mb
Release : 2007-06-21
Category : Science
ISBN : 9783540330257

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Astronomical Image and Data Analysis by J.-L. Starck,F. Murtagh Pdf

With information and scale as central themes, this comprehensive survey explains how to handle real problems in astronomical data analysis using a modern arsenal of powerful techniques. It treats those innovative methods of image, signal, and data processing that are proving to be both effective and widely relevant. The authors are leaders in this rapidly developing field and draw upon decades of experience. They have been playing leading roles in international projects such as the Virtual Observatory and the Grid. The book addresses not only students and professional astronomers and astrophysicists, but also serious amateur astronomers and specialists in earth observation, medical imaging, and data mining. The coverage includes chapters or appendices on: detection and filtering; image compression; multichannel, multiscale, and catalog data analytical methods; wavelets transforms, Picard iteration, and software tools. This second edition of Starck and Murtagh's highly appreciated reference again deals with topics that are at or beyond the state of the art. It presents material which is more algorithmically oriented than most alternatives and broaches new areas like ridgelet and curvelet transforms. Throughout the book various additions and updates have been made.