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Invitation to Law and Society - An Introduction to the Study of Real Law
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Algebraic Aspects of Cryptography (Algorithms and Computation in Mathematics) by Neal Koblitz (Repost)
Mathematics Mathematical Foundations of Computer Science 2004 [Repost]
Mathematics Mathematical Logic for Computer Science (3rd edition)
Physics Democracy and Public Space: The Physical Sites of Democratic Performance
Spaces of Holomorphic Functions in the Unit Ball (Graduate Texts in Mathematics) by Kehe Zhu (Repost)
An Introduction to Ergodic Theory (Graduate Texts in Mathematics) by Peter Walters (Repost)
Statistical and Thermal Physics - With Computer Applications
Introduction to the Physics of the Earth's Interior (Cambridge Topics in Mineral Ph) by Jean Paul Poirier (Repost)
Mathematics Symmetry Theory in Molecular Physics with Mathematica: A new kind of tutorial book (Repost)
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Study Computational Probability: Algorithms and Applications in the Mathematical Sciences
Posted on 2010-03-16
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More Computational Probability: Algorithms and Applications in the Mathematical Sciences, "Computational Probability: Algorithms and Applications in the Mathematical Sciences" Computational probability encompasses data structures and algorithms that have emerged over the past decade that allow researchers and students to focus on a new class of stochastic problems. "Computational Probability" is the first book that examines and presents these computational methods in a systematic manner. The techniques described here address problems that require exact probability calculations, many of which have been considered intractable in the past. The first chapter introduces computational probability analysis, followed by a chapter on the Maple computer algebra system. The third chapter begins the description of APPL, the probability modeling language created by the authors. The book ends with three applications-based chapters that emphasize applications in survival analysis and stochastic simulation. The algorithmic material associated with continuous random variables is presented separately from the material for discrete random variables. Four sample algorithms, which are implemented in APPL, are presented in detail: transformations of continuous random variables, products of independent continuous random variables, sums of independent discrete random variables, and order statistics drawn from discrete populations. The APPL computational modeling language gives the field of probability a strong software resource to use for non-trivial problems and is available at no cost from the authors. APPL is currently being used in applications as wide-ranging as electric power revenue forecasting, analyzing cortical spike trains, and studying the supersonic expansion of hydrogen molecules. Requests for the software have come from fields as diverse as market research, pathology, neurophysiology, statistics, engineering, psychology, physics, medicine, and chemistry. Not all books ... appear on the homepage. In order not to miss many of them follow Download Link (Ebooks section) (see top of each page on AH) and visit too :)
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