Measures, Integrals and Martingales

Measures, Integrals and Martingales PDF Author: René L. Schilling
Publisher: Cambridge University Press
ISBN: 1316620247
Category : Mathematics
Languages : en
Pages : 497

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Book Description
A concise, elementary introduction to measure and integration theory, requiring few prerequisites as theory is developed quickly and simply.

Measures, Integrals and Martingales

Measures, Integrals and Martingales PDF Author: René L. Schilling
Publisher: Cambridge University Press
ISBN: 1316620247
Category : Mathematics
Languages : en
Pages : 497

Get Book

Book Description
A concise, elementary introduction to measure and integration theory, requiring few prerequisites as theory is developed quickly and simply.

Measures, Integrals and Martingales

Measures, Integrals and Martingales PDF Author: René L. Schilling
Publisher: Cambridge University Press
ISBN: 9780521850155
Category : Mathematics
Languages : en
Pages : 404

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Book Description
This book, first published in 2005, introduces measure and integration theory as it is needed in many parts of analysis and probability.

Counterexamples in Measure and Integration

Counterexamples in Measure and Integration PDF Author: René L. Schilling
Publisher: Cambridge University Press
ISBN: 1009020390
Category : Mathematics
Languages : en
Pages : 431

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Book Description
Often it is more instructive to know 'what can go wrong' and to understand 'why a result fails' than to plod through yet another piece of theory. In this text, the authors gather more than 300 counterexamples - some of them both surprising and amusing - showing the limitations, hidden traps and pitfalls of measure and integration. Many examples are put into context, explaining relevant parts of the theory, and pointing out further reading. The text starts with a self-contained, non-technical overview on the fundamentals of measure and integration. A companion to the successful undergraduate textbook Measures, Integrals and Martingales, it is accessible to advanced undergraduate students, requiring only modest prerequisites. More specialized concepts are summarized at the beginning of each chapter, allowing for self-study as well as supplementary reading for any course covering measures and integrals. For researchers, it provides ample examples and warnings as to the limitations of general measure theory. This book forms a sister volume to René Schilling's other book Measures, Integrals and Martingales (www.cambridge.org/9781316620243).

Measure, Integral and Probability

Measure, Integral and Probability PDF Author: Marek Capinski
Publisher: Springer Science & Business Media
ISBN: 1447136314
Category : Mathematics
Languages : en
Pages : 229

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Book Description
This very well written and accessible book emphasizes the reasons for studying measure theory, which is the foundation of much of probability. By focusing on measure, many illustrative examples and applications, including a thorough discussion of standard probability distributions and densities, are opened. The book also includes many problems and their fully worked solutions.

Probability with Martingales

Probability with Martingales PDF Author: David Williams
Publisher: Cambridge University Press
ISBN: 9780521406055
Category : Mathematics
Languages : en
Pages : 274

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Book Description
This is a masterly introduction to the modern, and rigorous, theory of probability. The author emphasises martingales and develops all the necessary measure theory.

Measure theory and Integration

Measure theory and Integration PDF Author: G De Barra
Publisher: Elsevier
ISBN: 0857099523
Category : Mathematics
Languages : en
Pages : 240

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Book Description
This text approaches integration via measure theory as opposed to measure theory via integration, an approach which makes it easier to grasp the subject. Apart from its central importance to pure mathematics, the material is also relevant to applied mathematics and probability, with proof of the mathematics set out clearly and in considerable detail. Numerous worked examples necessary for teaching and learning at undergraduate level constitute a strong feature of the book, and after studying statements of results of the theorems, students should be able to attempt the 300 problem exercises which test comprehension and for which detailed solutions are provided. Approaches integration via measure theory, as opposed to measure theory via integration, making it easier to understand the subject Includes numerous worked examples necessary for teaching and learning at undergraduate level Detailed solutions are provided for the 300 problem exercises which test comprehension of the theorems provided

Martingales and Stochastic Integrals

Martingales and Stochastic Integrals PDF Author: P. E. Kopp
Publisher: Cambridge University Press
ISBN: 9780521090339
Category : Mathematics
Languages : en
Pages : 0

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Book Description
This book provides an introduction to the rapidly expanding theory of stochastic integration and martingales. The treatment is close to that developed by the French school of probabilists, but is more elementary than other texts. The presentation is abstract, but largely self-contained and Dr Kopp makes fewer demands on the reader's background in probability theory than is usual. He gives a fairly full discussion of the measure theory and functional analysis needed for martingale theory, and describes the role of Brownian motion and the Poisson process as paradigm examples in the construction of abstract stochastic integrals. An appendix provides the reader with a glimpse of very recent developments in non-commutative integration theory which are of considerable importance in quantum mechanics. Thus equipped, the reader will have the necessary background to understand research in stochastic analysis. As a textbook, this account will be ideally suited to beginning graduate students in probability theory, and indeed it has evolved from such courses given at Hull University. It should also be of interest to pure mathematicians looking for a careful, yet concise introduction to martingale theory, and to physicists, engineers and economists who are finding that applications to their disciplines are becoming increasingly important.

Measure, Integration & Real Analysis

Measure, Integration & Real Analysis PDF Author: Sheldon Axler
Publisher: Springer Nature
ISBN: 3030331431
Category : Mathematics
Languages : en
Pages : 430

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Book Description
This open access textbook welcomes students into the fundamental theory of measure, integration, and real analysis. Focusing on an accessible approach, Axler lays the foundations for further study by promoting a deep understanding of key results. Content is carefully curated to suit a single course, or two-semester sequence of courses, creating a versatile entry point for graduate studies in all areas of pure and applied mathematics. Motivated by a brief review of Riemann integration and its deficiencies, the text begins by immersing students in the concepts of measure and integration. Lebesgue measure and abstract measures are developed together, with each providing key insight into the main ideas of the other approach. Lebesgue integration links into results such as the Lebesgue Differentiation Theorem. The development of products of abstract measures leads to Lebesgue measure on Rn. Chapters on Banach spaces, Lp spaces, and Hilbert spaces showcase major results such as the Hahn–Banach Theorem, Hölder’s Inequality, and the Riesz Representation Theorem. An in-depth study of linear maps on Hilbert spaces culminates in the Spectral Theorem and Singular Value Decomposition for compact operators, with an optional interlude in real and complex measures. Building on the Hilbert space material, a chapter on Fourier analysis provides an invaluable introduction to Fourier series and the Fourier transform. The final chapter offers a taste of probability. Extensively class tested at multiple universities and written by an award-winning mathematical expositor, Measure, Integration & Real Analysis is an ideal resource for students at the start of their journey into graduate mathematics. A prerequisite of elementary undergraduate real analysis is assumed; students and instructors looking to reinforce these ideas will appreciate the electronic Supplement for Measure, Integration & Real Analysis that is freely available online. For errata and updates, visit https://measure.axler.net/

Measure, Integral, Probability & Processes

Measure, Integral, Probability & Processes PDF Author: René L Schilling
Publisher:
ISBN:
Category :
Languages : en
Pages : 450

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Book Description
In these lecture notes we give a self-contained and concise introduction to the essentials of modern probability theory. The material covers all concepts and techniques usually taught at BSc and first-year graduate level probability courses: Measure & integration theory, elementary probability theory, further probability, classic limit theorems, discrete-time and continuous-time martingales, Poisson processes, random walks & Markov chains and, finally, first steps towards Brownian motion. The text can serve as a course companion, for self study or as a reference text. Concepts, which will be useful for later chapters and further studies are introduced early on. The material is organized and presented in a way that will enable the readers to continue their study with any advanced text in probability theory, stochastic processes or stochastic analysis. Much emphasis is put on being reader-friendly and useful, giving a direct and quick start into a fascinating mathematical topic.

Real Analysis

Real Analysis PDF Author: J Yeh
Publisher: World Scientific Publishing Company
ISBN: 9814578568
Category : Mathematics
Languages : en
Pages : 840

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Book Description
This book presents a unified treatise of the theory of measure and integration. In the setting of a general measure space, every concept is defined precisely and every theorem is presented with a clear and complete proof with all the relevant details. Counter-examples are provided to show that certain conditions in the hypothesis of a theorem cannot be simply dropped. The dependence of a theorem on earlier theorems is explicitly indicated in the proof, not only to facilitate reading but also to delineate the structure of the theory. The precision and clarity of presentation make the book an ideal textbook for a graduate course in real analysis while the wealth of topics treated also make the book a valuable reference work for mathematicians. The book is also very helpful to graduate students in statistics and electrical engineering, two disciplines that apply measure theory.