Measure and probability

By: Siva AthreyaContributor(s): V. S. SunderPublication details: Boca Raton: CRC Press, [c2008]Description: 221 pISBN: 9781138114180Subject(s): MathematicsLOC classification: QA273.A87
Contents:
1. Probabilities and Measures 2. Integration 3. Random Variables 4. Probability Measures on Product Spaces 5. Characteristics and Convergences 6. Markov Chains 7. Some Analysis
Summary: This book covers the fundamentals of measure theory and probability theory. It begins with the construction of Lebesgue measure via Caratheodory’s outer measure approach and goes on to discuss integration and standard convergence theorems and contains an entire chapter devoted to complex measures, Lp spaces, Radon–Nikodym theorem, and the Riesz representation theorem. It presents the elements of probability theory, the law of large numbers, and central limit theorem. The book then discusses discrete time Markov chains, stationary distributions and limit theorems. The appendix covers many basic topics such as metric spaces, topological spaces and the Stone–Weierstrass theorem. --- summary provided by publisher
List(s) this item appears in: New Arrivals
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Item type Current library Collection Shelving location Call number Status Date due Barcode Item holds
Book Book ICTS
Mathematics Rack No 5 QA273.A87 (Browse shelf (Opens below)) Checked out to Elizabeth Sara Roy (0008456945) 12/02/2024 02863
Total holds: 0

1. Probabilities and Measures
2. Integration
3. Random Variables
4. Probability Measures on Product Spaces
5. Characteristics and Convergences
6. Markov Chains
7. Some Analysis

This book covers the fundamentals of measure theory and probability theory. It begins with the construction of Lebesgue measure via Caratheodory’s outer measure approach and goes on to discuss integration and standard convergence theorems and contains an entire chapter devoted to complex measures, Lp spaces, Radon–Nikodym theorem, and the Riesz representation theorem. It presents the elements of probability theory, the law of large numbers, and central limit theorem. The book then discusses discrete time Markov chains, stationary distributions and limit theorems. The appendix covers many basic topics such as metric spaces, topological spaces and the Stone–Weierstrass theorem. --- summary provided by publisher

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