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Practical Bayesian Inference
This book introduces the major concepts of probability and statistics, along with the necessary computational tools, for undergraduates and graduate students.
Practical Bayesian Inference
Science is fundamentally about learning from data, and doing so in the presence of uncertainty. This volume is an introduction to the major concepts of probability and statistics, and the computational tools for analysing and interpreting data. It describes the Bayesian approach, and explains how this can be used to fit and compare models in a range of problems. Topics covered include regression, parameter estimation, model assessment, and Monte Carlo methods, as well as widely used classical methods such as regularization and hypothesis testing. The emphasis throughout is on the principles, the unifying probabilistic approach, and showing how the methods can be implemented in practice. R code (with explanations) is included and is available online, so readers can reproduce the plots and results for themselves. Aimed primarily at undergraduate and graduate students, these techniques can be applied to a wide range of data analysis problems beyond the scope of this work.
Scientific Models in Philosophy of Science
Scientists have used models for hundreds of years as a means of describing phenomena and as a basis for further analogy. In Scientific Models in Philosophy of Science, Daniela Bailer-Jones assembles an original and comprehensive philosophical analysis of how models have been used and interpreted in both historical and contemporary contexts. Bailer-Jones delineates the many forms models can take (ranging from equations to animals; from physical objects to theoretical constructs), and how they are put to use. She examines early mechanical models employed by nineteenth-century physicists such as Kelvin and Maxwell, describes their roots in the mathematical principles of Newton and others, and c...
Classification and Discovery in Large Astronomical Surveys
Astronomical surveys produce large amounts of photometric, spectroscopic and time-series data. Object classification, parameter determination, novelty detection and the discovery of structure in these are challenging tasks. This book, featuring contributions from both astronomers and computer scientists, discusses a broad range of astronomical problems and shows how various machine learining and statistical analysis techniques are being used to solve them.
Principal Manifolds for Data Visualization and Dimension Reduction
The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering algorithms, principal manifolds and SOM. New approaches to NLPCA, principal manifolds, branching principal components and topology preserving mappings are described. Presentation of algorithms is supplemented by case studies. The volume ends with a tutorial PCA deciphers genome.
Highlights of Astronomy: Volume 14
Recording the proceedings of the IAU XXVI General Assembly, this volume of the IAU Highlights of Astronomy covers virtually all aspects of modern astrophysics as discussed by 2400 participants from 73 countries. Notably, the common aspects of astrophysical phenomena known to exist in widely differing interstellar environments is thoroughly examined, providing fertile cross correlation from one specialisation to another. This text highlights the importance of the triennial IAU General Assemblies in bringing together the work of observers and theoreticians in widely different fields, but working towards a common goal: understanding the physics of the Universe. Together with the Proceedings of the IAU Symposia 235-240, this volume examines all of the astrophysics presented at the General Assembly.
Transits of Venus (IAU C196)
IAU C196 coincided with the 8 June 2004 transit of Venus, producing the exciting, eclectic mix that can be found in these proceedings: the amazing history of the English North-country astronomers of the seventeenth century; the AU at a precision of 1.4 m; the explanation for the infamous black drop effect; a possible Mayan observation of a transit of Venus in the thirteenth century; the vexed question of leap seconds and time scales; history, distances, parallaxes, the solar system at exquisite precision and future space missions that will revolutionise astronomy.
Classification - the Ubiquitous Challenge
The contributions in this volume represent the latest research results in the field of Classification, Clustering, and Data Analysis. Besides the theoretical analysis, papers focus on various application fields as Archaeology, Astronomy, Bio-Sciences, Business, Electronic Data and Web, Finance and Insurance, Library Science and Linguistics, Marketing, Music Science, and Quality Assurance.
Model-Based Reasoning
There are several key ingredients common to the various forms of model-based reasoning considered in this book. The term ‘model’ comprises both internal and external representations. The models are intended as interpretations of target physical systems, processes, phenomena, or situations and are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. The book’s contributors are researchers active in the area of creative reasoning in science and technology.
