Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

For the Second Edition of this highly regarded textbook, Gerald Edgar has made numerous additions and changes, in an attempt to provide a clearer and more focused exposition. The most important addition is an increased emphasis on the packing measure, so that now it is often treated on a par with the Hausdorff measure. The topological dimensions were rearranged for Chapter 3, so that the covering dimension is the major one, and the inductive dimensions are the variants. A "reduced cover class" notion was introduced to help in proofs for Method I or Method II measures. Research results since 1990 that affect these elementary topics have been taken into account. Some examples have been added, including Barnsley leaf and Julia set, and most of the figures have been re-drawn. From reviews of the First Edition: "...there has been a deluge of books, articles and television programmes about the beautiful mathematical objects, drawn by computers using recursive or iterative algorithms, which Mandelbrot christened fractals. Gerald Edgar's book is a significant addition to this deluge. Based on a course given to talented high-school students at Ohio University in 1988, it is, in fact, an advanced undergraduate textbook about the mathematics of fractal geometry, treating such topics as metric spaces, measure theory, dimension theory, and even some algebraic topology...the book also contains many good illustrations of fractals..." - Mathematics Teaching "The book can be recommended to students who seriously want to know about the mathematical foundation of fractals, and to lecturers who want to illustrate a standard course in metric topology by interesting examples." - Christoph Bandt, Mathematical Reviews "...not only intended to fit mathematics students who wish to learn fractal geometry from its beginning but also students in computer science who are interested in the subject. [For such students] the author gives the required topics from metric topology and measure theory on an elementary level. The book is written in a very clear style and contains a lot of exercises which should be worked out." - H.Haase, Zentralblatt

analyse (wiskunde) --- Geometry --- Differential geometry. Global analysis --- topologie --- Mathematical physics --- differentiaalvergelijkingen --- Mathematical analysis --- Topology --- geometrie --- Measure theory. Mathematical integration --- Fractals --- Measure theory

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This is a graduate level textbook on measure theory and probability theory. The book can be used as a text for a two semester sequence of courses in measure theory and probability theory, with an option to include supplemental material on stochastic processes and special topics. It is intended primarily for first year Ph.D. students in mathematics and statistics although mathematically advanced students from engineering and economics would also find the book useful. Prerequisites are kept to the minimal level of an understanding of basic real analysis concepts such as limits, continuity, differentiability, Riemann integration, and convergence of sequences and series. A review of this material is included in the appendix. The book starts with an informal introduction that provides some heuristics into the abstract concepts of measure and integration theory, which are then rigorously developed. The first part of the book can be used for a standard real analysis course for both mathematics and statistics Ph.D. students as it provides full coverage of topics such as the construction of Lebesgue-Stieltjes measures on real line and Euclidean spaces, the basic convergence theorems, Lp spaces, signed measures, Radon-Nikodym theorem, Lebesgue's decomposition theorem and the fundamental theorem of Lebesgue integration on R, product spaces and product measures, and Fubini-Tonelli theorems. It also provides an elementary introduction to Banach and Hilbert spaces, convolutions, Fourier series and Fourier and Plancherel transforms. Thus part I would be particularly useful for students in a typical Statistics Ph.D. program if a separate course on real analysis is not a standard requirement. Part II (chapters 6-13) provides full coverage of standard graduate level probability theory. It starts with Kolmogorov's probability model and Kolmogorov's existence theorem. It then treats thoroughly the laws of large numbers including renewal theory and ergodic theorems with applications and then weak convergence of probability distributions, characteristic functions, the Levy-Cramer continuity theorem and the central limit theorem as well as stable laws. It ends with conditional expectations and conditional probability, and an introduction to the theory of discrete time martingales. Part III (chapters 14-18) provides a modest coverage of discrete time Markov chains with countable and general state spaces, MCMC, continuous time discrete space jump Markov processes, Brownian motion, mixing sequences, bootstrap methods, and branching processes. It could be used for a topics/seminar course or as an introduction to stochastic processes. Krishna B. Athreya is a professor at the departments of mathematics and statistics and a Distinguished Professor in the College of Liberal Arts and Sciences at the Iowa State University. He has been a faculty member at University of Wisconsin, Madison; Indian Institute of Science, Bangalore; Cornell University; and has held visiting appointments in Scandinavia and Australia. He is a fellow of the Institute of Mathematical Statistics USA; a fellow of the Indian Academy of Sciences, Bangalore; an elected member of the International Statistical Institute; and serves on the editorial board of several journals in probability and statistics. Soumendra N. Lahiri is a professor at the department of statistics at the Iowa State University. He is a fellow of the Institute of Mathematical Statistics, a fellow of the American Statistical Association, and an elected member of the International Statistical Institute.

Measure theory --- Probabilities --- Integrals, Generalized --- Stochastic processes --- Measure theory. Mathematical integration --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Lebesgue measure --- Measurable sets --- Measure of a set --- Algebraic topology --- Measure algebras --- Rings (Algebra) --- Calculus, Integral --- 303.3 --- AA / International- internationaal --- Waarschijnlijkheid. Probabiliteit. Nauwkeurigheid. Residuals: measurement and specification (wiskundige statistiek)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

A paean to twentieth century analysis, this modern text has several important themes and key features which set it apart from others on the subject. A major thread throughout is the unifying influence of the concept of absolute continuity on differentiation and integration. This leads to fundamental results such as the Dieudonné–Grothendieck theorem and other intricate developments dealing with weak convergence of measures. Key Features: * Fascinating historical commentary interwoven into the exposition; * Hundreds of problems from routine to challenging; * Broad mathematical perspectives and material, e.g., in harmonic analysis and probability theory, for independent study projects; * Two significant appendices on functional analysis and Fourier analysis. Key Topics: * In-depth development of measure theory and Lebesgue integration; * Comprehensive treatment of connection between differentiation and integration, as well as complete proofs of state-of-the-art results; * Classical real variables and introduction to the role of Cantor sets, later placed in the modern setting of self-similarity and fractals; * Evolution of the Riesz representation theorem to Radon measures and distribution theory; * Deep results in modern differentiation theory; * Systematic development of weak sequential convergence inspired by theorems of Vitali, Nikodym, and Hahn–Saks; * Thorough treatment of rearrangements and maximal functions; * The relation between surface measure and Hausforff measure; * Complete presentation of Besicovich coverings and differentiation of measures. Integration and Modern Analysis will serve advanced undergraduates and graduate students, as well as professional mathematicians. It may be used in the classroom or self-study.

Mathematics. --- Analysis. --- Functions of a Complex Variable. --- Measure and Integration. --- Global analysis (Mathematics). --- Functions of complex variables. --- Mathématiques --- Analyse globale (Mathématiques) --- Fonctions d'une variable complexe --- Mathematical analysis --- Functions of real variables --- Integration, Functional --- Integrals, Generalized --- Measure theory --- Electronic books. -- local. --- Functions of real variables. --- Integrals, Generalized. --- Integration, Functional. --- Mathematical analysis. --- Measure theory. --- Engineering & Applied Sciences --- Applied Mathematics --- Lebesgue measure --- Measurable sets --- Measure of a set --- 517.1 Mathematical analysis --- Functional integration --- Real variables --- Analysis (Mathematics). --- Algebraic topology --- Measure algebras --- Rings (Algebra) --- Functional analysis --- Calculus, Integral --- Functions of complex variables --- Analysis, Global (Mathematics) --- Differential topology --- Geometry, Algebraic

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book offers a panorama of recent advances in the theory of infinite groups. It contains survey papers contributed by leading specialists in group theory and other areas of mathematics. Topics addressed in the book include amenable groups, Kaehler groups, automorphism groups of rooted trees, rigidity, C*-algebras, random walks on groups, pro-p groups, Burnside groups, parafree groups, and Fuchsian groups. The accent is put on strong connections between group theory and other areas of mathematics, such as dynamical systems, geometry, operator algebras, probability theory, and others. This interdisciplinary approach makes the book interesting to a large mathematical audience. Contributors: G. Baumslag A.V. Borovik T. Delzant W. Dicks E. Formanek R. Grigorchuk M. Gromov P. de la Harpe A. Lubotzky W. Lück A.G. Myasnikov C. Pache G. Pisier A. Shalev S. Sidki E. Zelmanov.

Infinite groups. --- Ergodic theory. --- Selfadjoint operators. --- Differential topology. --- Geometry, Differential --- Topology --- Operators, Selfadjoint --- Self-adjoint operators --- Linear operators --- Ergodic transformations --- Continuous groups --- Mathematical physics --- Measure theory --- Transformations (Mathematics) --- Groups, Infinite --- Group theory --- Group theory. --- Topological Groups. --- Combinatorics. --- Operator theory. --- Global differential geometry. --- Algebraic topology. --- Group Theory and Generalizations. --- Topological Groups, Lie Groups. --- Operator Theory. --- Differential Geometry. --- Algebraic Topology. --- Functional analysis --- Combinatorics --- Algebra --- Mathematical analysis --- Groups, Topological --- Groups, Theory of --- Substitutions (Mathematics) --- Topological groups. --- Lie groups. --- Differential geometry. --- Differential geometry --- Groups, Lie --- Lie algebras --- Symmetric spaces --- Topological groups

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Devoted to a theory of gradient flows in spaces which are not necessarily endowed with a natural linear or differentiable structure, this book focuses on gradient flows in metric spaces. It covers gradient flows in the space of probability measures on a separable Hilbert space, endowed with the Kantorovich-Rubinstein-Wasserstein distance.

Differential geometry. Global analysis --- Mathematical physics --- Operational research. Game theory --- differentiaalvergelijkingen --- kansrekening --- differentiaal geometrie --- stochastische analyse --- Measure theory --- Metric spaces --- Differential equations, Partial --- Monotone operators --- Evolution equations, Nonlinear --- Mesure, Théorie de la --- Espaces métriques --- Equations aux dérivées partielles --- Opérateurs monotones --- Equations d'évolution non linéaires --- EPUB-LIV-FT LIVMATHE LIVSTATI SPRINGER-B --- Global analysis (Mathematics). --- Mathematics. --- Global differential geometry. --- Distribution (Probability theory. --- Analysis. --- Measure and Integration. --- Differential Geometry. --- Probability Theory and Stochastic Processes. --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Geometry, Differential --- Math --- Science --- Analysis, Global (Mathematics) --- Differential topology --- Functions of complex variables --- Geometry, Algebraic --- Mathematical analysis. --- Analysis (Mathematics). --- Measure theory. --- Differential geometry. --- Probabilities. --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Differential geometry --- Lebesgue measure --- Measurable sets --- Measure of a set --- Algebraic topology --- Integrals, Generalized --- Measure algebras --- Rings (Algebra) --- 517.1 Mathematical analysis --- Mathematical analysis --- Metric spaces. --- Differential equations, Parabolic. --- Monotone operators. --- Evolution equations, Nonlinear. --- Operator theory --- Parabolic differential equations --- Parabolic partial differential equations --- Spaces, Metric --- Generalized spaces --- Set theory --- Topology --- Nonlinear equations of evolution --- Nonlinear evolution equations --- Differential equations, Nonlinear