Stokastik

This third edition is a revised, updated, and greatly expanded version of previous edition of 2001. The 1300+ exercises contained within are not merely drill problems, but have been chosen to illustrate the concepts, illuminate the subject, and bo...

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Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists...

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When properly applied, randomness can be a powerful tool in programming, science, and art. This highly practical but geekily fun introduction to randomness shows you how to put chaos to work, illustrating its ability to power everything from the s...

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Das Buch wendet sich vor allem an Mathematik-Lehrkräfte aller Schularten, aber auch an Lehramts-Studierende und Referendare. Praxisnah und gut lesbar geschrieben, vermittelt dieses Werk einen Einblick in die Stochastik für den Mathematikunterricht...

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This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing¿in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many example...

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*Textbook and Academic Authors Association (TAA) McGuffey Longevity Award Winner, 2024* A trusted market leader for four decades, Sheldon Ross's Introduction to Probability Models offers a comprehensive foundation of this key subject with applicat...

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Dieses Lehrbuch befasst sich leicht verständlich mit der Theorie der Kalman-Filterung. Die Autoren geben damit eine Einführung in Kalman-Filter und deren Anwendung für eingebettete Systeme. Zusätzlich wird anhand konkreter Praxisbeispiele der Kalm...

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Learn traditional and cutting-edge machine learning (ML) and deep learning techniques and best practices for time series forecasting, including global forecasting models, conformal prediction, and transformer architectures Key Features Apply ML an...

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The purpose of this book is to provide the reader with a solid background and understanding of the basic results and methods in probability theory before entering into more advanced courses (in probability and/or statistics). The presentation is f...

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The fourth edition of this successful text provides an introduction to probability and random processes, with many practical applications. It is aimed at mathematics undergraduates and postgraduates, and has four main aims. US BL To provide a thor...

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Band 5 umfaßt die Themenbereiche Astronomie, Optik und Wahrscheinlichkeitstheorie. Er enthält Hausdorffs Dissertation über die Refraktion des Lichtes in der Atmosphäre, zwei Folgearbeiten zum gleichen Thema sowie die Habilitationsschrift über die ...

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Simulation, Sixth Edition continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers...

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Completely revised and greatly expanded, the new edition of this text takes readers who have been exposed to only basic courses in analysis through the modern general theory of random processes and stochastic integrals as used by systems theorists...

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A key aspect of robotics today is estimating the state (e.g., position and orientation) of a robot, based on noisy sensor data. This book targets students and practitioners of robotics by presenting classical state estimation methods (e.g., the Ka...

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This book offers an introduction to the mathematical, probabilistic and numerical methods used in the modern theory of option pricing. The text is designed for readers with a basic mathematical background. The first part contains a presentation of...

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An introduction to stochastic processes through the use of R Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probabil...

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This graduate text presents the elegant and profound theory of continuous parameter Markov processes and many of its applications.¿ The authors focus on developing context and intuition before formalizing the theory of each topic, illustrated with...

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The purpose of this book is to provide the reader with a solid background and understanding of the basic results and methods in probability theory before entering into more advanced courses (in probability and/or statistics). The presentation is f...

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Of what use is mathematics? Hasn't everything in mathematics already been disc- ered? Thesearenaturalquestionsoftenaskedbyundergraduates. Theanswersprovided by their professors are often quite brief. Most university courses, pressed for time and r...

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This is a somewhat extended and modified translation of the third edition of the text, first published in 1969. The Swedish edition has been used for many years at the Royal Institute of Technology in Stockholm, and at the School of Engineering at...

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Discrete-time Stochastic Systems gives a comprehensive introduction to the estimation and control of dynamic stochastic systems and provides complete derivations of key results such as the basic relations for Wiener filtering. The book covers both...

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The fourth edition of this widely used textbook on pricing and hedging of financial derivatives now also includes dynamic equilibrium theory and continues to combine sound mathematical principles with economic applications. Concentrating on the pr...

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This book presents a concise and rigorous treatment of stochastic calculus. It also gives its main applications in finance, biology and engineering. In finance, the stochastic calculus is applied to pricing options by no arbitrage. In biology, it ...

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This book introduces the reader to Six Sigma, a problem-solving technique for reducing defects and variation in processes. The author uses DMAIC phases (Define, Measure, Analyze, Improve and Control) and a data-centric approach, leveraging applied...

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Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists...

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This is an introduction to Bayesian statistics and decision theory, including advanced topics such as Monte Carlo methods. This new edition contains several revised chapters and a new chapter on model choice.

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Geometric Data Analysis (GDA) is the name suggested by P. Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by Benzécri as Correspondence Analysis, an approach that has become more and more used and apprec...

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Covering formulation, algorithms, and structural results, and linking theory to real-world applications in controlled sensing (including social learning, adaptive radars and sequential detection), this book focuses on the conceptual foundations of...

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An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes necessary in understanding and applying stochastic methods to biological problems in areas such as population gr...

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Advanced Mathematical Tools for Automatic Control Engineers, Volume 2: Stochastic Techniques provides comprehensive discussions on statistical tools for control engineers. The book is divided into four main parts. Part I discusses the fundamentals...

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