Measure theory.

Measures on infinite dimensional spaces / by: (Language materials, printed)

Measure theory / by: (Language materials, printed)

Quantum measures and spaces / by: (Language materials, printed)

Measure and integration : = an advanced course in basic procedures and applications / by: (Language materials, printed)

Measure, integral and probability / by: (Language materials, printed)

Fuzzy measure theory / by: (Language materials, printed)

Lectures on amenability / by: (Language materials, printed)

Measures with symmetry properties / by: (Language materials, printed)

Integral, probability, and fractal measures / by: (Language materials, printed)

The Banach-Tarski paradox / by: (Language materials, printed)

Measure, integration, and functional analysis / by: (Language materials, printed)

Measure theory / by: (Language materials, printed)

Theory of function spaces III / by: (Language materials, printed)

Measure and integral : = an introduction to real analysis / by: (Language materials, printed)

Measure theory and integration / by: (Language materials, printed)

A first look at rigorous probability theory / by: (Language materials, printed)

Measures, integrals and martingales / by: (Language materials, printed)

Tame geometry with application in smooth analysis by: (Electronic resources)

Thermodynamic formalism and holomorphic dynamical systems / by: (Language materials, printed)

An Introduction to measure theory / by: (Language materials, printed)

Handbook of measure theory by: (Electronic resources)

The Elements of Cantor sets : = with applications / by: (Language materials, printed)

A course on integration theory = including more than 150 exercises with detailed answers / by: (Electronic resources)

The elements of Cantor sets = with applications / by: (Electronic resources)

A Basic course in measure and probability : = theory for applications / by: (Language materials, printed)

An introduction to measure-theoretic probability by: (Electronic resources)

Measure and integration by: (Electronic resources)

Analysis on Gaussian spaces by: (Electronic resources)

Universal measurements = how to free three birds in one move / by: (Electronic resources)

Repeated measurements and cross-over designs by: (Electronic resources)

Probability and conditional expectation = fundamentals for the empirical sciences / by: (Electronic resources)

Measure and integration by: (Electronic resources)

Fourier analysis and Hausdorff dimension by: (Electronic resources)

Gibbs states on countable sets by: (Electronic resources)

Measure, integration and a primer on probability theory.. Volume 1 by: (Electronic resources)

Combined measure and shift invariance theory of time scales and applications by: (Electronic resources)

Notes on real analysis and measure theory = fine properties of real sets and functions / by: (Electronic resources)

Measure theory and integration by: (Electronic resources)

Measure-theoretic calculus in abstract spaces = on the playground of infinite-dimensional spaces / by: (Electronic resources)

Classical and discrete functional analysis with measure theory by: (Electronic resources)

Lectures on the theory of integration / by: (Language materials, printed)

An introduction to integration and measure theory / by: (Language materials, printed)

Real analysis : = theory of measure and integration / by: (Language materials, printed)

Lebesgue integration on Euclidean space by: (Language materials, printed)

Measure and integration. by: (Language materials, printed)

Measure theory / by: (Language materials, printed)

Measure and integral / by: (Language materials, printed)

Probability and measure / by: (Language materials, printed)

Contiguity and the statistical invariance principle / by: (Language materials, printed)

Measure theory / by: (Language materials, printed)

Non-additive measure and integral / by: (Language materials, printed)

Probability and measure / by: (Language materials, printed)

Measure, topology, and fractal geometry / by: (Language materials, printed)

Probability and measure / by: (Language materials, printed)

Integration : = a functional approach / by: (Language materials, printed)

Measures and probabilities / by: (Language materials, printed)

Advanced integration theory / by: (Language materials, printed)

The Elements of integration and Lebesgue measure / by: (Language materials, printed)

Loeb measures in practice : = recent advances / by: (Language materials, printed)

A first look at rigorous probability theory / by: (Language materials, printed)

Stochastic optimal control : = the discrete-time case / by: (Language materials, printed)

Tame geometry with application in smooth analysis / by: (Language materials, printed)

Measure, integral and probability / by: (Language materials, printed)

Real analysis : = measure theory, integration, and Hilbert spaces / by: (Language materials, printed)

Ergodic theory via joinings / by: (Language materials, printed)

Gradient flows : = in metric spaces and in the space of probability measures / by: (Language materials, printed)

Gradient Flows = in Metric Spaces and in the Space of Probability Measures / by: (Language materials, printed)

Measure, Topology, and Fractal Geometry by: (Language materials, printed)

Weak convergence of measures = applications in probability / by: (Language materials, printed)

Gradient flows = in metric spaces and in the space of probability measures / by: (Language materials, printed)

Lebesgue measure and integration : = an introduction / by: (Language materials, printed)

Measure theory and integration / by: (Language materials, printed)

Real analysis / by: (Language materials, printed)

Topics in measure theory and real analysis / by: (Language materials, printed)

Measures with symmetry properties by: (Language materials, printed)

Gradient flows : = in metric spaces and in the space of probability measures / by: (Language materials, printed)

Measure theory : = a first course / by: (Language materials, printed)

Measure and integration = an advanced course in basic procedures and applications / by: (Language materials, printed)

Probability, random processes, and ergodic properties by: (Language materials, printed)

Generalized measure theory by: (Language materials, printed)

Gibbs measures and phase transitions / by: (Language materials, printed)

Real analysis / by: (Language materials, printed)

Essentials of integration theory for analysis / by: (Language materials, printed)

Denumerable Markov chains : = generating functions, boundary theory, random walks on trees / by: (Language materials, printed)

Reifenberg parameterizations for sets with holes / by: (Language materials, printed)

The Borel-Cantelli Lemma by: (Electronic resources)

A Course in abstract analysis / by: (Language materials, printed)

A Course on integration theory : = including more than 150 exercises with detailed answers / by: (Language materials, printed)

Measure and Integral by: (Electronic resources)

Introduction to measure theory and functional analysis / by: (Language materials, printed)

Fourier analysis and Hausdorff dimension / by: (Language materials, printed)

Measure and integral : = an introduction to real analysis / by: (Language materials, printed)

Essentials of measure theory by: (Electronic resources)

Measure theory and fine properties of functions / by: (Language materials, printed)

Fundamentals of functional analysis by: (Electronic resources)

Analysis = from concepts to applications / by: (Electronic resources)

Applications of measure theory to statistics by: (Electronic resources)

Probability and conditional expectation : = fundamentals for the empirical sciences / by: (Language materials, printed)

A basic course in measure and probability = theory for applications / by: (Electronic resources)

A course in functional analysis and measure theory by: (Electronic resources)

Metric in measure spaces / by: (Language materials, printed)

Density evolution under delayed dynamics = an open problem / by: (Electronic resources)

Essentials of integration theory for analysis by: (Electronic resources)

Measure theory, probability, and stochastic processes by: (Electronic resources)

Regular non-additive multimeasures = fundaments and applications / by: (Electronic resources)