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Author : Joseph M. Hilbe,Rafael S. de Souza,Emille E. O. Ishida
Publisher : Cambridge University Press
Page : 429 pages
File Size : 45,8 Mb
Release : 2017-04-27
Category : Mathematics
ISBN : 9781107133082
A hands-on guide to Bayesian models with R, JAGS, Python, and Stan code, for a wide range of astronomical data types.
Author : Luis Manuel Sarro,Laurent Eyer,William O'Mullane,Joris De Ridder
Publisher : Springer Science & Business Media
Page : 259 pages
File Size : 54,7 Mb
Release : 2012-08-04
Category : Science
ISBN : 9781461433231
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.
Author : Andrés Asensio Ramos,Iñigo Arregui
Publisher : Unknown
Page : 128 pages
File Size : 48,6 Mb
Release : 2018
Category : Astronomy
ISBN : 1107499585
"Bayesian methods are increasingly being employed in many different areas of physical sciences research. In astrophysics, models are used to make predictions to compare to observations that are incomplete and uncertain, so the comparison must be pursued by following a probabilistic approach. With contributions from leading experts, this volume covers the foundations of Bayesian inference, a description of the applicable computational methods, and recent results from their application to areas such as exoplanet detection and characterisation, image reconstruction, and cosmology. With content that appeals both to young researchers seeking to learn about Bayesian methods and to astronomers wishing to incorporate these approaches into their research, it provides the next generation of researchers with tools of modern data analysis that are becoming standard in astrophysical research"--
Author : Michael P. Hobson
Publisher : Cambridge University Press
Page : 317 pages
File Size : 55,6 Mb
Release : 2010
Category : Mathematics
ISBN : 9780521887946
Comprehensive introduction to Bayesian methods in cosmological studies, for graduate students and researchers in cosmology, astrophysics and applied statistics.
Author : Phil Gregory
Publisher : Cambridge University Press
Page : 498 pages
File Size : 48,7 Mb
Release : 2005-04-14
Category : Mathematics
ISBN : 9781139444286
Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at www.cambridge.org/9780521150125.
Author : Stefano Andreon,Brian Weaver
Publisher : Springer
Page : 238 pages
File Size : 50,7 Mb
Release : 2015-05-19
Category : Mathematics
ISBN : 9783319152875
Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications. This book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics. Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University
Author : Joseph M. Hilbe
Publisher : Springer Science & Business Media
Page : 247 pages
File Size : 41,9 Mb
Release : 2012-11-07
Category : Mathematics
ISBN : 9781461435082
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
Author : Eric D. Feigelson,Jogesh Babu
Publisher : Springer Science & Business Media
Page : 506 pages
File Size : 53,9 Mb
Release : 2006-05-26
Category : Science
ISBN : 9780387215297
Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches. The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects. The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales.
Author : Eric D. Feigelson,Jogesh Babu
Publisher : Springer Science & Business Media
Page : 559 pages
File Size : 44,9 Mb
Release : 2012-08-15
Category : Mathematics
ISBN : 9781461435204
This volume contains a selection of chapters based on papers to be presented at the Fifth Statistical Challenges in Modern Astronomy Symposium. The symposium will be held June 13-15th at Penn State University. Modern astronomical research faces a vast range of statistical issues which have spawned a revival in methodological activity among astronomers. The Statistical Challenges in Modern Astronomy V conference will bring astronomers and statisticians together to discuss methodological issues of common interest. Time series analysis, image analysis, Bayesian methods, Poisson processes, nonlinear regression, maximum likelihood, multivariate classification, and wavelet and multiscale analyses are all important themes to be covered in detail. Many problems will be introduced at the conference in the context of large-scale astronomical projects including LIGO, AXAF, XTE, Hipparcos, and digitized sky surveys.
Author : Marisa Cristina March
Publisher : Springer Science & Business Media
Page : 193 pages
File Size : 43,5 Mb
Release : 2013-01-13
Category : Science
ISBN : 9783642350603
This thesis explores advanced Bayesian statistical methods for extracting key information for cosmological model selection, parameter inference and forecasting from astrophysical observations. Bayesian model selection provides a measure of how good models in a set are relative to each other - but what if the best model is missing and not included in the set? Bayesian Doubt is an approach which addresses this problem and seeks to deliver an absolute rather than a relative measure of how good a model is. Supernovae type Ia were the first astrophysical observations to indicate the late time acceleration of the Universe - this work presents a detailed Bayesian Hierarchical Model to infer the cosmological parameters (in particular dark energy) from observations of these supernovae type Ia.
Author : Joseph M. Hilbe
Publisher : CRC Press
Page : 174 pages
File Size : 55,8 Mb
Release : 2016-04-05
Category : Mathematics
ISBN : 9781498709583
Practical Guide to Logistic Regression covers the key points of the basic logistic regression model and illustrates how to use it properly to model a binary response variable. This powerful methodology can be used to analyze data from various fields, including medical and health outcomes research, business analytics and data science, ecology, fisheries, astronomy, transportation, insurance, economics, recreation, and sports. By harnessing the capabilities of the logistic model, analysts can better understand their data, make appropriate predictions and classifications, and determine the odds of one value of a predictor compared to another. Drawing on his many years of teaching logistic regression, using logistic-based models in research, and writing about the subject, Professor Hilbe focuses on the most important features of the logistic model. Serving as a guide between the author and readers, the book explains how to construct a logistic model, interpret coefficients and odds ratios, predict probabilities and their standard errors based on the model, and evaluate the model as to its fit. Using a variety of real data examples, mostly from health outcomes, the author offers a basic step-by-step guide to developing and interpreting observation and grouped logistic models as well as penalized and exact logistic regression. He also gives a step-by-step guide to modeling Bayesian logistic regression. R statistical software is used throughout the book to display the statistical models while SAS and Stata codes for all examples are included at the end of each chapter. The example code can be adapted to readers’ own analyses. All the code is available on the author’s website.
Author : Joseph M. Hilbe
Publisher : Cambridge University Press
Page : 301 pages
File Size : 55,8 Mb
Release : 2014-07-21
Category : Business & Economics
ISBN : 9781107028333
"This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of linear regression and works up to an analysis of the Poisson and negative binomial models, and to the problem of overdispersion. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in public health, ecology, econometrics, transportation, and other related fields"--
Author : Eric D. Feigelson,G. Jogesh Babu
Publisher : Cambridge University Press
Page : 495 pages
File Size : 45,6 Mb
Release : 2012-07-12
Category : Science
ISBN : 9780521767279
Modern Statistical Methods for Astronomy: With R Applications.
Author : Omar Benhar,Alessandro Lovato,Andrea Maselli,Francesco Pannarale
Publisher : CRC Press
Page : 481 pages
File Size : 48,6 Mb
Release : 2024-07-03
Category : Science
ISBN : 9781040044766
Over the last decade, astrophysical observations of neutron stars — both as isolated and binary sources — have paved the way for a deeper understanding of the structure and dynamics of matter beyond nuclear saturation density. The mapping between astrophysical observations and models of dense matter based on microscopic dynamics has been poorly investigated so far. However, the increased accuracy of present and forthcoming observations may be instrumental in resolving the degeneracy between the predictions of different equations of state. Astrophysical and laboratory probes have the potential to paint to a new coherent picture of nuclear matter — and, more generally, strong interactions — over the widest range of densities occurring in the Universe. This book provides a self-contained account of neutron star properties, microscopic nuclear dynamics and the recent observational developments in multimessenger astronomy. It also discusses the unprecedented possibilities to shed light on long standing and fundamental issues, such as the validity of the description of matter in terms of pointlike baryons and leptons and the appearance of deconfined quarks in the high density regime. It will be of interest to researchers and advanced PhD students working in the fields of Astrophysics, Gravitational Physics, Nuclear Physics and Particle Physics. Key Features: Reviews state-of-the-art theoretical and experimental developments Self-contained and cross-disciplinary While being devoted to a very lively and fast developing field, the book fundamentally addresses methodological issues. Therefore, it will not be subject to fast obsolescence. Omar Benhar is an INFN Emeritus Research Director, and has been teaching Relativistic Quantum Mechanics, Quantum Electrodynamics and Structure of Compact Stars at “Sapienza” University of Rome for over twenty years. He has worked extensively in the United States, and since 2013 has served as an adjunct professor at the Center for Neutrino Physics of Virginia Polytechnic Institute and State University. Prof. Benhar has authored or co-authored three textbooks on Relativistic Quantum Mechanics, Gauge Theories, and Structure and Dynamics of Compact Stars, and published more than one hundred scientific papers on the theory of many-particle systems, the structure of compact stars and the electroweak interactions of nuclei. Alessandro Lovato is a physicist at Argonne National Laboratory and an INFN researcher in Trento. His research in theoretical nuclear physics focuses on consistently modeling the self-emerging properties of atomic nuclei and neutron-star matter in terms of the microscopic interactions among the constituent protons and neutrons. He has co-authored more than eighty scientific publications on the theory of many-particle systems, the structure of compact stars, and the electroweak interactions of nuclei. He is at the forefront of high-performance computing applied to solving the quantum many-body problem. Andrea Maselli is an Associate Professor at the Gran Sasso Science Institute, in L’Aquila, where he teaches Gravitation and Cosmology and Physics of Black Hole. His research focuses on strong gravity, which plays a crucial role in many astrophysical phenomena involving black hole and neutron stars, representing natural laboratories to test fundamental physics. Prof. Maselli has co-authored more than eighty scientific papers on the modelling of black holes and neutron stars in General Relativity and extension thereof, their gravitational wave emission, and on tests of gravity in the strong filed regime. He is active in various collaborations aimed at developing next generation of gravitational wave detectors, such as the LISA satellite, the Einstein Telescope, and the Lunar Gravitational Wave Antenna. Francesco Pannarale is an Associate Professor at “Sapienza” Univeristy of Rome, where he teaches Gravitational Waves, Compact Objects and Black Holes, Computing Methods for Physics, and Electromagnetism. His research interests are in gravitational-wave physics and multimessenger astronomy, and they range from modelling compact binary sources to data analysis. He has co-authored over one hundred and eighty scientific publications and was at the forefront of the joint observation of GW170817 and GRB 170817A. He is currently serving as co-chair of the LIGO-Virgo-KAGRA Data Analysis Council.
Author : Bertrand Zavidovique,Giosu Lo Bosco
Publisher : World Scientific
Page : 328 pages
File Size : 54,7 Mb
Release : 2012
Category : Science
ISBN : 9789814383288
The book gathers articles that were exposed during the seventh edition of the Workshop ?Data Analysis in Astronomy?. It illustrates a current trend to search for common expressions or models transcending usual disciplines, possibly associated with some lack in the Mathematics required to model complex systems. In that, data analysis would be at the epicentre and a key facilitator of some current integrative phase of Science.It is all devoted to the question of ?representation in Science?, whence its name, IMAGe IN AcTION, and main thrusts Part A: Information: data organization and communication, Part B: System: structure and behaviour, Part C: Data ? System representation. Such a classification makes concepts as ?complexity? or ?dynamics? appear like transverse notions: a measure among others or a dimensional feature among others.Part A broadly discusses a dialogue between experiments and information, be information extracted-from or brought-to experiments. The concept is fundamental in statistics and tailors to the emergence of collective behaviours. Communication then asks for uncertainty considerations ? noise, indeterminacy or approximation ? and its wider impact on the couple perception-action. Clustering being all about uncertainty handling, data set representation appears not to be the only solution: Introducing hierarchies with adapted metrics, a priori pre-improving the data resolution are other methods in need of evaluation. The technology together with increasing semantics enables to involve synthetic data as simulation results for the multiplication of sources.Part B plays with another couple important for complex systems: state vs. transition. State-first descriptions would characterize physics, while transition-first would fit biology. That could stem from life producing dynamical systems in essence. Uncertainty joining causality here, geometry can bring answers: stable patterns in the state space involve constraints from some dynamics consistency. Stable patterns of activity characterize biological systems too. In the living world, the complexity ? i.e. a global measure on both states and transitions ? increases with consciousness: this might be a principle of evolution. Beside geometry or measures, operators and topology have supporters for reporting on dynamical systems. Eventually targeting universality, the category theory of topological thermodynamics is proposed as a foundation of dynamical system understanding.Part C details examples of actual data-system relations in regards to explicit applications and experiments. It shows how pure computer display and animation techniques link models and representations to ?reality? in some ?concrete? virtual, manner. Such techniques are inspired from artificial life, with no connection to physical, biological or physiological phenomena! The Virtual Observatory is the second illustration of the evidence that simulation helps Science not only in giving access to more flexible parameter variability, but also due to the associated data and method storing-capabilities. It fosters interoperability, statistics on bulky corpuses, efficient data mining possibly through the web etc. in short a reuse of resources in general, including novel ideas and competencies. Other examples deal more classically with inverse modelling and reconstruction, involving Bayesian techniques or chaos but also fractal and symmetry.