Measure, Integral and Probability

Measure, Integral and Probability
Author: Marek Capinski
Publisher: Springer Science & Business Media
Total Pages: 229
Release: 2013-06-29
Genre: Mathematics
ISBN: 1447136314

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.

Measure, Integral, Probability & Processes

Measure, Integral, Probability & Processes
Author: René L Schilling
Publisher:
Total Pages: 450
Release: 2021-02-02
Genre:
ISBN:

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.

Integration, Measure and Probability

Integration, Measure and Probability
Author: H. R. Pitt
Publisher: Courier Corporation
Total Pages: 130
Release: 2012-01-01
Genre: Mathematics
ISBN: 0486488152

Introductory treatment develops the theory of integration in a general context, making it applicable to other branches of analysis. More specialized topics include convergence theorems and random sequences and functions. 1963 edition.

Measure, Integration and a Primer on Probability Theory

Measure, Integration and a Primer on Probability Theory
Author: Stefano Gentili
Publisher: Springer Nature
Total Pages: 458
Release: 2020-11-30
Genre: Mathematics
ISBN: 3030549402

The text contains detailed and complete proofs and includes instructive historical introductions to key chapters. These serve to illustrate the hurdles faced by the scholars that developed the theory, and allow the novice to approach the subject from a wider angle, thus appreciating the human side of major figures in Mathematics. The style in which topics are addressed, albeit informal, always maintains a rigorous character. The attention placed in the careful layout of the logical steps of proofs, the abundant examples and the supplementary remarks disseminated throughout all contribute to render the reading pleasant and facilitate the learning process. The exposition is particularly suitable for students of Mathematics, Physics, Engineering and Statistics, besides providing the foundation essential for the study of Probability Theory and many branches of Applied Mathematics, including the Analysis of Financial Markets and other areas of Financial Engineering.

Measures, Integrals and Martingales

Measures, Integrals and Martingales
Author: René L. Schilling
Publisher: Cambridge University Press
Total Pages: 404
Release: 2005-11-10
Genre: Mathematics
ISBN: 9780521850155

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

Probability and Measure

Probability and Measure
Author: Patrick Billingsley
Publisher: John Wiley & Sons
Total Pages: 612
Release: 2017
Genre:
ISBN: 9788126517718

Now in its new third edition, Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Retaining the unique approach of the previous editions, this text interweaves material on probability and measure, so that probability problems generate an interest in measure theory and measure theory is then developed and applied to probability. Probability and Measure provides thorough coverage of probability, measure, integration, random variables and expected values, convergence of distributions, derivatives and conditional probability, and stochastic processes. The Third Edition features an improved treatment of Brownian motion and the replacement of queuing theory with ergodic theory.· Probability· Measure· Integration· Random Variables and Expected Values· Convergence of Distributions· Derivatives and Conditional Probability· Stochastic Processes

Counterexamples in Measure and Integration

Counterexamples in Measure and Integration
Author: René L. Schilling
Publisher: Cambridge University Press
Total Pages: 431
Release: 2021-06-17
Genre: Mathematics
ISBN: 1009020390

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).

A Basic Course in Measure and Probability

A Basic Course in Measure and Probability
Author: Ross Leadbetter
Publisher: Cambridge University Press
Total Pages: 375
Release: 2014-01-30
Genre: Mathematics
ISBN: 1107020409

A concise introduction covering all of the measure theory and probability most useful for statisticians.

Introduction to Measure Theory and Integration

Introduction to Measure Theory and Integration
Author: Luigi Ambrosio
Publisher: Springer Science & Business Media
Total Pages: 193
Release: 2012-02-21
Genre: Mathematics
ISBN: 8876423869

This textbook collects the notes for an introductory course in measure theory and integration. The course was taught by the authors to undergraduate students of the Scuola Normale Superiore, in the years 2000-2011. The goal of the course was to present, in a quick but rigorous way, the modern point of view on measure theory and integration, putting Lebesgue's Euclidean space theory into a more general context and presenting the basic applications to Fourier series, calculus and real analysis. The text can also pave the way to more advanced courses in probability, stochastic processes or geometric measure theory. Prerequisites for the book are a basic knowledge of calculus in one and several variables, metric spaces and linear algebra. All results presented here, as well as their proofs, are classical. The authors claim some originality only in the presentation and in the choice of the exercises. Detailed solutions to the exercises are provided in the final part of the book.

An Introduction to Measure and Probability

An Introduction to Measure and Probability
Author: J.C. Taylor
Publisher: Springer Science & Business Media
Total Pages: 316
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461206596

Assuming only calculus and linear algebra, Professor Taylor introduces readers to measure theory and probability, discrete martingales, and weak convergence. This is a technically complete, self-contained and rigorous approach that helps the reader to develop basic skills in analysis and probability. Students of pure mathematics and statistics can thus expect to acquire a sound introduction to basic measure theory and probability, while readers with a background in finance, business, or engineering will gain a technical understanding of discrete martingales in the equivalent of one semester. J. C. Taylor is the author of numerous articles on potential theory, both probabilistic and analytic, and is particularly interested in the potential theory of symmetric spaces.