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Modern Statistical Methods For Astronomy


Modern Statistical Methods For Astronomy
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Modern Statistical Methods For Astronomy


Modern Statistical Methods For Astronomy
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Author : Eric D. Feigelson
language : en
Publisher: Cambridge University Press
Release Date : 2012-07-12

Modern Statistical Methods For Astronomy written by Eric D. Feigelson and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-12 with Science categories.


Modern Statistical Methods for Astronomy: With R Applications.



Fundamentals Of Modern Statistical Methods


Fundamentals Of Modern Statistical Methods
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Author : Rand R. Wilcox
language : en
Publisher: Springer
Release Date : 2010-03-10

Fundamentals Of Modern Statistical Methods written by Rand R. Wilcox and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-10 with Social Science categories.


Conventional statistical methods have a very serious flaw. They routinely miss differences among groups or associations among variables that are detected by more modern techniques, even under very small departures from normality. Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable. Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods. Without assuming the reader has any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand. The emphasis is on verbal and graphical descriptions of concepts. Part II describes modern methods that address the problems covered in Part I. Using data from actual studies, many examples are included to illustrate the practical problems with conventional procedures and how more modern methods can make a substantial difference in the conclusions reached in many areas of statistical research. The second edition of this book includes a number of advances and insights that have occurred since the first edition appeared. Included are new results relevant to medians, regression, measures of association, strategies for comparing dependent groups, methods for dealing with heteroscedasticity, and measures of effect size.



Modern Statistical Methods For Astronomy


Modern Statistical Methods For Astronomy
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Author : Eric D. Feigelson
language : en
Publisher:
Release Date : 2012

Modern Statistical Methods For Astronomy written by Eric D. Feigelson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Statistical astronomy categories.


"Modern astronomical research is beset with a vast range of statistical challenges, ranging from reducing data from megadatasets to characterizing an amazing variety of variable celestial objects or testing astrophysical theory. Yet most astronomers still use a narrow suite of traditional statistical methods. Linking astronomy to the world of modern statistics, this volume is a unique resource, introducing astronomers to advanced statistics through ready-to-use code in the public-domain R statistical software environment."--



Astrostatistics


Astrostatistics
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Author : Gutti Jogesh Babu
language : en
Publisher: CRC Press
Release Date : 1996-08-01

Astrostatistics written by Gutti Jogesh Babu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-08-01 with Mathematics categories.


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.



Statistics Data Mining And Machine Learning In Astronomy


Statistics Data Mining And Machine Learning In Astronomy
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Author : Željko Ivezić
language : en
Publisher: Princeton University Press
Release Date : 2014-01-12

Statistics Data Mining And Machine Learning In Astronomy written by Željko Ivezić and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-12 with Science categories.


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



Astronomical Image And Data Analysis


Astronomical Image And Data Analysis
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Author : J.-L. Starck
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-21

Astronomical Image And Data Analysis written by J.-L. Starck and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-21 with Science categories.


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.



Statistical Analysis Of Circular Data


Statistical Analysis Of Circular Data
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Author : N. I. Fisher
language : en
Publisher: Cambridge University Press
Release Date : 1995-10-12

Statistical Analysis Of Circular Data written by N. I. Fisher and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-10-12 with Mathematics categories.


A unified, up-to-date account of circular data-handling techniques, useful throughout science.



Statistical Analysis Of Spherical Data


Statistical Analysis Of Spherical Data
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Author : N. I. Fisher
language : en
Publisher: Cambridge University Press
Release Date : 1993-08-19

Statistical Analysis Of Spherical Data written by N. I. Fisher and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-08-19 with Mathematics categories.


This is the first comprehensive, yet clearly presented, account of statistical methods for analysing spherical data. The analysis of data, in the form of directions in space or of positions of points on a spherical surface, is required in many contexts in the earth sciences, astrophysics and other fields, yet the methodology required is disseminated throughout the literature. Statistical Analysis of Spherical Data aims to present a unified and up-to-date account of these methods for practical use. The emphasis is on applications rather than theory, with the statistical methods being illustrated throughout the book by data examples.



Statistical Methods For Climate Scientists


Statistical Methods For Climate Scientists
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Author : Timothy DelSole
language : en
Publisher: Cambridge University Press
Release Date : 2022-02-24

Statistical Methods For Climate Scientists written by Timothy DelSole and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-24 with Mathematics categories.


An accessible introduction to statistical methods for students in the climate sciences.



Applying Contemporary Statistical Techniques


Applying Contemporary Statistical Techniques
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Author : Rand R. Wilcox
language : en
Publisher: Elsevier
Release Date : 2003-01-16

Applying Contemporary Statistical Techniques written by Rand R. Wilcox and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-01-16 with Mathematics categories.


Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible.* Assumes no previous training in statistics * Explains how and why modern statistical methods provide more accurate results than conventional methods* Covers the latest developments on multiple comparisons * Includes recent advances in risk-based methods * Features many illustrations and examples using data from real studies * Describes and illustrates easy-to-use s-plus functions for applying cutting-edge techniques * Covers many contemporary ANOVA (analysis of variance) and regression methods not found in other books