Bayesian Methods For The Physical Sciences

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Bayesian Methods For The Physical Sciences

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Author : Stefano Andreon
language : en
Publisher: Springer
Release Date : 2015-05-19

Bayesian Methods For The Physical Sciences written by Stefano Andreon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-19 with Mathematics categories.

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

Bayesian Methods For The Physical Sciences

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Author : Elijah Joshua
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-06-12

Bayesian Methods For The Physical Sciences written by Elijah Joshua and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-12 with categories.

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.

Bayesian Logical Data Analysis For The Physical Sciences

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Author : Phil Gregory
language : en
Publisher: Cambridge University Press
Release Date : 2005-04-14

Bayesian Logical Data Analysis For The Physical Sciences written by Phil Gregory 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 2005-04-14 with Mathematics categories.

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.

Statistical Methods For Physical Science

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Author :
language : en
Publisher: Academic Press
Release Date : 1994-12-13

Statistical Methods For Physical Science written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-12-13 with Science categories.

This volume of Methods of Experimental Physics provides an extensive introduction to probability and statistics in many areas of the physical sciences, with an emphasis on the emerging area of spatial statistics. The scope of topics covered is wide-ranging-the text discusses a variety of the most commonly used classical methods and addresses newer methods that are applicable or potentially important. The chapter authors motivate readers with their insightful discussions. - Examines basic probability, including coverage of standard distributions, time series models, and Monte Carlo methods - Describes statistical methods, including basic inference, goodness of fit, maximum likelihood, and least squares - Addresses time series analysis, including filtering and spectral analysis - Includes simulations of physical experiments - Features applications of statistics to atmospheric physics and radio astronomy - Covers the increasingly important area of modern statistical computing

Bayesian Theory And Applications

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Author : Paul Damien
language : en
Publisher: Oxford University Press
Release Date : 2013-01-24

Bayesian Theory And Applications written by Paul Damien and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-24 with Mathematics categories.

This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field.

Bayesian Compendium

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Author : Marcel van Oijen
language : en
Publisher: Springer Nature
Release Date : 2024-08-27

Bayesian Compendium written by Marcel van Oijen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-27 with Mathematics categories.

This book describes how Bayesian methods work. Aiming to demystify the approach, it explains how to parameterize and compare models while accounting for uncertainties in data, model parameters and model structures. Bayesian thinking is not difficult and can be used in virtually every kind of research. How exactly should data be used in modelling? The literature offers a bewildering variety of techniques (Bayesian calibration, data assimilation, Kalman filtering, model-data fusion, ...). This book provides a short and easy guide to all these approaches and more. Written from a unifying Bayesian perspective, it reveals how these methods are related to one another. Basic notions from probability theory are introduced and executable R codes for modelling, data analysis and visualization are included to enhance the book’s practical use. The codes are also freely available online. This thoroughly revised second edition has separate chapters on risk analysis and decision theory. It also features an expanded text on machine learning with an introduction to natural language processing and calibration of neural networks using various datasets (including the famous iris and MNIST). Literature references have been updated and exercises with solutions have doubled in number.

Sensor Technologies For Civil Infrastructures Volume 2

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Author : Jerome P. Lynch
language : en
Publisher: Elsevier
Release Date : 2014-05-19

Sensor Technologies For Civil Infrastructures Volume 2 written by Jerome P. Lynch and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-19 with Technology & Engineering categories.

Sensors are used for civil infrastructure performance assessment and health monitoring, and have evolved significantly through developments in materials and methodologies. Sensor Technologies for Civil Infrastructure Volume II provides an overview of sensor data analysis and case studies in assessing and monitoring civil infrastructures. Part one focuses on sensor data interrogation and decision making, with chapters on data management technologies, data analysis, techniques for damage detection and structural damage detection. Part two is made up of case studies in assessing and monitoring specific structures such as bridges, towers, buildings, dams, tunnels, pipelines, and roads. Sensor Technologies for Civil Infrastructure provides a standard reference for structural and civil engineers, electronics engineers, and academics with an interest in the field. - Provides an in-depth examination of sensor data management and analytical techniques for fault detection and localization, looking at prognosis and life-cycle assessment - Includes case studies in assessing structures such as bridges, buildings, super-tall towers, dams, tunnels, wind turbines, railroad tracks, nuclear power plants, offshore structures, levees, and pipelines

Computational Problems In Engineering

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Author : Nikos Mastorakis
language : en
Publisher: Springer
Release Date : 2014-06-04

Computational Problems In Engineering written by Nikos Mastorakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-04 with Technology & Engineering categories.

This book provides readers with modern computational techniques for solving variety of problems from electrical, mechanical, civil and chemical engineering. Mathematical methods are presented in a unified manner, so they can be applied consistently to problems in applied electromagnetics, strength of materials, fluid mechanics, heat and mass transfer, environmental engineering, biomedical engineering, signal processing, automatic control and more.

Statistical Challenges In Modern Astronomy V

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Author : Eric D. Feigelson
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-08-15

Statistical Challenges In Modern Astronomy V written by Eric D. Feigelson 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 2012-08-15 with Mathematics categories.

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.

Data Analysis For Scientists And Engineers

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Author : Edward L. Robinson
language : en
Publisher: Princeton University Press
Release Date : 2016-09-20

Data Analysis For Scientists And Engineers written by Edward L. Robinson 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 2016-09-20 with Science categories.

Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix. Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. In-depth discussion of data analysis for scientists and engineers Coverage of both frequentist and Bayesian approaches to data analysis Extensive look at analysis techniques for time-series data and images Detailed exploration of linear and nonlinear modeling of data Emphasis on error analysis Instructor's manual (available only to professors)