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An introduction to Crystallography


Издание на английском языке.Kleber Will "An introduction to Crystallography", VeB Verlag Technik, Berlin, 1970.Will Kleber is the author of numerous publications among which the book An Introduction to Crystallography takes a prominent place.Книга посвящена кристаллографии.

174 RUR
Kleber W.

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Paul Gagniuc A. Markov Chains. From Theory to Implementation and Experimentation


A fascinating and instructive guide to Markov chains for experienced users and newcomers alike This unique guide to Markov chains approaches the subject along the four convergent lines of mathematics, implementation, simulation, and experimentation. It introduces readers to the art of stochastic modeling, shows how to design computer implementations, and provides extensive worked examples with case studies. Markov Chains: From Theory to Implementation and Experimentation begins with a general introduction to the history of probability theory in which the author uses quantifiable examples to illustrate how probability theory arrived at the concept of discrete-time and the Markov model from experiments involving independent variables. An introduction to simple stochastic matrices and transition probabilities is followed by a simulation of a two-state Markov chain. The notion of steady state is explored in connection with the long-run distribution behavior of the Markov chain. Predictions based on Markov chains with more than two states are examined, followed by a discussion of the notion of absorbing Markov chains. Also covered in detail are topics relating to the average time spent in a state, various chain configurations, and n-state Markov chain simulations used for verifying experiments involving various diagram configurations. • Fascinating historical notes shed light on the key ideas that led to the development of the Markov model and its variants • Various configurations of Markov Chains and their limitations are explored at length • Numerous examples—from basic to complex—are presented in a comparative manner using a variety of color graphics • All algorithms presented can be analyzed in either Visual Basic, Java Script, or PHP • Designed to be useful to professional statisticians as well as readers without extensive knowledge of probability theory Covering both the theory underlying the Markov model and an array of Markov chain implementations, within a common conceptual framework, Markov Chains: From Theory to Implementation and Experimentation is a stimulating introduction to and a valuable reference for those wishing to deepen their understanding of this extremely valuable statistical tool. Paul A. Gagniuc, PhD, is Associate Professor at Polytechnic University of Bucharest, Romania. He obtained his MS and his PhD in genetics at the University of Bucharest. Dr. Gagniuc’s work has been published in numerous high profile scientific journals, ranging from the Public Library of Science to BioMed Central and Nature journals. He is the recipient of several awards for exceptional scientific results and a highly active figure in the review process for different scientific areas.

8998.6 RUR

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Poggiolini Laura A First Course in Probability and Markov Chains


Provides an introduction to basic structures of probability with a view towards applications in information technology A First Course in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores notions and structures in probability, including combinatorics, probability measures, probability distributions, conditional probability, inclusion-exclusion formulas, random variables, dispersion indexes, independent random variables as well as weak and strong laws of large numbers and central limit theorem. In the second part of the book, focus is given to Discrete Time Discrete Markov Chains which is addressed together with an introduction to Poisson processes and Continuous Time Discrete Markov Chains. This book also looks at making use of measure theory notations that unify all the presentation, in particular avoiding the separate treatment of continuous and discrete distributions. A First Course in Probability and Markov Chains: Presents the basic elements of probability. Explores elementary probability with combinatorics, uniform probability, the inclusion-exclusion principle, independence and convergence of random variables. Features applications of Law of Large Numbers. Introduces Bernoulli and Poisson processes as well as discrete and continuous time Markov Chains with discrete states. Includes illustrations and examples throughout, along with solutions to problems featured in this book. The authors present a unified and comprehensive overview of probability and Markov Chains aimed at educating engineers working with probability and statistics as well as advanced undergraduate students in sciences and engineering with a basic background in mathematical analysis and linear algebra.

7312.36 RUR

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Jochen Voss An Introduction to Statistical Computing. A Simulation-based Approach


A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course

7078.99 RUR

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Elizabeth Rayhel A. Introduction to One Health. An Interdisciplinary Approach to Planetary Health


Introduction to One Health: An Interdisciplinary Approach to Planetary Health offers an accessible, readable introduction to the burgeoning field of One Health. Provides a thorough introduction to the who, what, where, when, why, and how of One Health Presents an overview of the One Health movement viewed through the perspective of different disciplines Encompasses disease ecology, conservation, and veterinary and human medicine Includes interviews from persons across disciplines important for the success of One Health Includes case studies in each chapter to demonstrate real-world applications

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Daniel Arrigo J. Symmetry Analysis of Differential Equations. An Introduction


A self-contained introduction to the methods and techniques of symmetry analysis used to solve ODEs and PDEs Symmetry Analysis of Differential Equations: An Introduction presents an accessible approach to the uses of symmetry methods in solving both ordinary differential equations (ODEs) and partial differential equations (PDEs). Providing comprehensive coverage, the book fills a gap in the literature by discussing elementary symmetry concepts and invariance, including methods for reducing the complexity of ODEs and PDEs in an effort to solve the associated problems. Thoroughly class-tested, the author presents classical methods in a systematic, logical, and well-balanced manner. As the book progresses, the chapters graduate from elementary symmetries and the invariance of algebraic equations, to ODEs and PDEs, followed by coverage of the nonclassical method and compatibility. Symmetry Analysis of Differential Equations: An Introduction also features: Detailed, step-by-step examples to guide readers through the methods of symmetry analysis End-of-chapter exercises, varying from elementary to advanced, with select solutions to aid in the calculation of the presented algorithmic methods Symmetry Analysis of Differential Equations: An Introduction is an ideal textbook for upper-undergraduate and graduate-level courses in symmetry methods and applied mathematics. The book is also a useful reference for professionals in science, physics, and engineering, as well as anyone wishing to learn about the use of symmetry methods in solving differential equations.

6899.07 RUR

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Martin D. Daniel Martin 


Set internationally and spanning three decades. Daniel Martin is. among other things. an exploration of what it is to be English. Daniel is a screenwriter working in Hollywood. who finds himself dissatisfied with his career and with the person he has become. In a richly evoked narrative. Daniel travels home to reconcile with a dying friend. and also to visit his own forgotten past in an attempt to discover himself.

910 RUR

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William Webb Solutions Manual to accompany Combinatorial Reasoning: An Introduction to the Art of Counting


This is a solutions manual to accompany Combinatorial Reasoning: An Introduction to the Art of Counting Written by well-known scholars in the field, Combinatorial Reasoning: An Introduction to the Art of Counting introduces combinatorics alongside modern techniques, showcases the interdisciplinary aspects of the topic, and illustrates how to problem solve with a multitude of exercises throughout. The authors' approach is very reader-friendly and avoids the «scholarly tone» found in many books on this topic.

2325.06 RUR

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Stefan G. Hofmann An Introduction to Modern CBT. Psychological Solutions to Mental Health Problems


An Introduction to Modern CBT provides an easily accessible introduction to modern theoretical cognitive behavioral therapy models. The text outlines the different techniques, their success in improving specific psychiatric disorders, and important new developments in the field. • Provides an easy-to-read introduction into modern Cognitive Behavioral Therapy approaches with specific case examples and hands-on treatment techniques • Discusses the theoretical models of CBT, outlines the different techniques that have been shown to be successful in improving specific psychiatric disorders, and describes important new developments in the field • Offers useful guidance for therapists in training and is an invaluable reference tool for experienced clinicians

2174.26 RUR

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Carl Graham Markov Chains. Analytic and Monte Carlo Computations


Markov Chains: Analytic and Monte Carlo Computations introduces the main notions related to Markov chains and provides explanations on how to characterize, simulate, and recognize them. Starting with basic notions, this book leads progressively to advanced and recent topics in the field, allowing the reader to master the main aspects of the classical theory. This book also features: Numerous exercises with solutions as well as extended case studies. A detailed and rigorous presentation of Markov chains with discrete time and state space. An appendix presenting probabilistic notions that are necessary to the reader, as well as giving more advanced measure-theoretic notions.

8923.18 RUR

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