Achim Klenke – författare

This second edition of the popular textbook contains a comprehensive course in modern probability theory, covering a wide variety of topics which are not usually found in introductory textbooks, including: • limit theorems for sums of random variables• martingales• percolation• Markov chains and electrical networks• construction of stochastic processes• Poisson point process and infinite divisibility• large deviation principles and statistical physics• Brownian motion• stochastic integral and stochastic differential equations.

The theory is developed rigorously and in a self-contained way, with the chapters on measure theory interlaced with the probabilistic chapters in order to display the power of the abstract concepts in probability theory. This second edition has been carefully extended and includes many new features. It contains updated figures (over 50), computer simulations and some difficult proofs have been made more accessible. A wealth of examples and more than 270 exercises as well as biographic details of key mathematicians support and enliven the presentation. It will be of use to students and researchers in mathematics and statistics in physics, computer science, economics and biology.

Aimed primarily at graduate students and researchers, this text is a comprehensive course in modern probability theory and its measure-theoretical foundations. It covers a wide variety of topics, many of which are not usually found in introductory textbooks, such as: limit theorems for sums of random variables; martingales; percolation; Markov chains and electrical networks; construction of stochastic processes; Poisson point processes and infinite divisibility; large deviation principles and statistical physics; Brownian motion; and stochastic integral and stochastic differential equations.

The theory is developed rigorously and in a self-contained way, with the chapters on measure theory interlaced with the probabilistic chapters in order to display the power of the abstract concepts in the world of probability theory. In addition, plenty of figures, computer simulations, biographic details of key mathematicians, and a wealth of examples support and enliven the presentation.

Probability plays an increasingly important role not only in mathematics, but also in physics, biology, finance and computer science, helping to understand phenomena such as magnetism, genetic diversity and market volatility, and also to construct efficient algorithms. Starting with the very basics, this textbook covers a wide variety of topics in probability, including many not usually found in introductory books, such as:

This third edition has been carefully extended and includes new features, such as concise summaries at the end of each section and additional questions to encourage self-reflection, as well as updates to the figures and computer simulations. With a wealth of examples and more than 290 exercises, as well as biographical details of key mathematicians, it will be of use to students and researchers in mathematics, statistics, physics, computer science, economics and biology.

Dieses Lehrbuch bietet eine umfassende moderne Einführung in die wichtigsten Gebiete der Wahrscheinlichkeitstheorie und ihre maßtheoretischen Grundlagen. Themenschwerpunkte sind: Maß- und Integrationstheorie, Grenzwertsätze für Summen von Zufallsvariablen (Gesetze der Großen Zahl, Zentraler Grenzwertsatz, Ergodensätze, Gesetz vom iterierten Logarithmus, Invarianzprinzipien, unbegrenzt teilbare Verteilungen), Martingale, Perkolation, Markovketten und elektrische Netzwerke, Konstruktion stochastischer Prozesse, Poisson''scher Punktprozess, Brown''sche Bewegung, stochastisches Integral und stochastische Differentialgleichungen. Mehr als 250 Übungsaufgaben und zahlreiche Abbildungen runden die Darstellung ab. Breite und Auswahl der Themen sind einmalig in der deutschsprachigen Literatur.

Dieses Lehrbuch bietet eine umfassende moderne Einführung in die wichtigsten Gebiete der Wahrscheinlichkeitstheorie und ihre maßtheoretischen Grundlagen. Themenschwerpunkte sind: Maß- und Integrationstheorie, Grenzwertsätze für Summen von Zufallsvariablen (Gesetze der Großen Zahl, Zentraler Grenzwertsatz, Ergodensätze, Gesetz vom iterierten Logarithmus, Invarianzprinzipien, unbegrenzt teilbare Verteilungen), Martingale, Perkolation, Markovketten und elektrische Netzwerke, Konstruktion stochastischer Prozesse, Poisson''scher Punktprozess, Brown''sche Bewegung, stochastisches Integral und stochastische Differentialgleichungen. Mehr als 250 Übungsaufgaben und zahlreiche Abbildungen runden die Darstellung ab. Breite und Auswahl der Themen sind einmalig in der deutschsprachigen Literatur.