Cart
Free US shipping over $10
Proud to be B-Corp

An Introduction to Measure and Probability J.C. Taylor

An Introduction to Measure and Probability By J.C. Taylor

An Introduction to Measure and Probability by J.C. Taylor


$49.47
Condition - Good
Only 1 left

Summary

Assuming only calculus and linear algebra, Professor Taylor introduces readers to measure theory and probability, discrete martingales, and weak convergence.

Faster Shipping

Get this product faster from our US warehouse

An Introduction to Measure and Probability Summary

An Introduction to Measure and Probability by J.C. Taylor

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.

Table of Contents

I. Probability Spaces.- 1. Introduction to ?.- 2. What is a probability space? Motivation.- 3. Definition of a probability space.- 4. Construction of a probability from a distribution function.- 5. Additional exercises*.- II. Integration.- 1. Integration on a probability space.- 2. Lebesgue measure on ? and Lebesgue integration.- 3. The Riemann integral and the Lebesgue integral.- 4. Probability density functions.- 5. Infinite series again.- 6. Differentiation under the integral sign.- 7. Signed measures and the Radon-Nikodym theorem*.- 8. Signed measures on ? and functions of bounded variation*.- 9. Additional exercises*.- III. Independence and Product Measures.- 1. Random vectors and Borel sets in ?n.- 2. Independence.- 3. Product measures.- 4. Infinite products.- 5. Some remarks on Markov chains*.- 6. Additional exercises*.- IV. Convergence of Random Variables and Measurable Functions.- 1. Norms for random variables and measurable functions.- 2. Continuous functions and Lp*.- 3. Pointwise convergence and convergence in measure or probability.- 4. Kolmogorov's inequality and the strong law of large numbers.- 5. Uniform integrability and truncation*.- 6. Differentiation: the Hardy-Littlewood maximal function*.- 7. Additional exercises*.- V. Conditional Expectation and an Introduction to Martingales.- 1. Conditional expectation and Hilbert space.- 2. Conditional expectation.- 3. Sufficient statistics*.- 4. Martingales.- 5. An introduction to martingale convergence.- 6. The three-series theorem and the Doob decomposition.- 7. The martingale convergence theorem.- VI. An Introduction to Weak Convergence.- 1. Motivation: empirical distributions.- 2. Weak convergence of probabilities: equivalent formulations.- 3. Weak convergence of random variables.- 4. Empirical distributions again: the Glivenko-Cantelli theorem.- 5. The characteristic function.- 6. Uniqueness and inversion of the characteristic function.- 7. The central limit theorem.- 8. Additional exercises*.- 9. Appendix*.

Additional information

CIN0387948309G
9780387948300
0387948309
An Introduction to Measure and Probability by J.C. Taylor
Used - Good
Paperback
Springer-Verlag New York Inc.
1998-07-31
324
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in good condition, but if you are not entirely satisfied please get in touch with us

Customer Reviews - An Introduction to Measure and Probability