<span><p><i>An Introduction to Measure-Theoretic Probability, Second Edition</i>, employs a classical approach to teaching the basics of measure theoretic probability. This book provides in a concise, yet detailed way, the bulk of the probabilistic tools that a student working toward an advanced deg
An introduction to measure-theoretic probability
โ Scribed by Roussas, George G
- Publisher
- Academic Press
- Year
- 2014
- Tongue
- English
- Leaves
- 557
- Edition
- 2nd Edition
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Certain classes of sets, measurability, and pointwise approximation -- Definition and construction of a measure and its basic properties -- Some modes of convergence of sequences of random variables and their relationships -- The integral of a random variable and its basic properties -- Standard convergence theorems, the Fubini theorem -- Standard moment and probability inequalities, convergence in the rth mean and its implications -- The Hahn-Jordan decomposition theorem, the Lebesgue decomposition theorem, and the Radon-Nikodym theorem -- Distribution functions and their basic properties, Helly-Bray type results -- Conditional expectation and conditional probability, and related properties and results -- Independence -- Topics from the theory of characteristic functions -- The central limit problem: the centered case -- The central limit problem: the noncentered case -- Topics from sequences of independent random variables -- Topics from Ergodic theory -- Two cases of statistical inference: estimation of a real-valued parameter, nonparametric estimation of a probability density function -- Appendixes: A. Brief review of chapters 1-16 -- B. Brief review of Riemann-Stieltjes integral -- C. Notation and abbreviations.;"In this introductory chapter, the concepts of a field and of a [sigma]-field are introduced, they are illustrated bymeans of examples, and some relevant basic results are derived. Also, the concept of a monotone class is defined and its relationship to certain fields and [sigma]-fields is investigated. Given a collection of measurable spaces, their product space is defined, and some basic properties are established. The concept of a measurable mapping is introduced, and its relation to certain [sigma]-fields is studied. Finally, it is shown that any random variable is the pointwise limit of a sequence of simple random variables"--
โฆ Table of Contents
Certain classes of sets, measurability, and pointwise approximation --
Definition and construction of a measure and its basic properties --
Some modes of convergence of sequences of random variables and their relationships --
The integral of a random variable and its basic properties --
Standard convergence theorems, the Fubini theorem --
Standard moment and probability inequalities, convergence in the rth mean and its implications --
The Hahn-Jordan decomposition theorem, the Lebesgue decomposition theorem, and the Radon-Nikodym theorem --
Distribution functions and their basic properties, Helly-Bray type results --
Conditional expectation and conditional probability, and related properties and results --
Independence --
Topics from the theory of characteristic functions --
The central limit problem: the centered case --
The central limit problem: the noncentered case --
Topics from sequences of independent random variables --
Topics from Ergodic theory --
Two cases of statistical inference: estimation of a real-valued parameter, nonparametric estimation of a probability density function --
Appendixes: A. Brief review of chapters 1-16 --
B. Brief review of Riemann-Stieltjes integral --
C. Notation and abbreviations.
โฆ Subjects
Measure theory;Probabilities;Electronic books
๐ SIMILAR VOLUMES
Certain classes of sets, measurability, and pointwise approximation -- Definition and construction of a measure and its basic properties -- Some modes of convergence of sequences of random variables and their relationships -- The integral of a random variable and its basic properties -- Standard con
"In this introductory chapter, the concepts of a field and of a [sigma]-field are introduced, they are illustrated bymeans of examples, and some relevant basic results are derived. Also, the concept of a monotone class is defined and its relationship to certain fields and [sigma]-fields is investiga
<p><i><b>An Introduction to Measure-Theoretic Probability</b></i>, Second Edition, employs a classical approach to teaching students of statistics, mathematics, engineering, econometrics, finance, and other disciplines measure-theoretic probability. This book requires no prior knowledge of measure t
<p>Assuming only calculus and linear algebra, this book introduces the reader in a technically complete way to measure theory and probability, discrete martingales, and weak convergence. It is self- contained and rigorous with a tutorial approach that leads the reader to develop basic skills in anal