Probability Theory

Tomas Cipra ()
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Tomas Cipra: Charles University of Prague, Dept. of Statistics, Faculty of Mathematics and Physics

Chapter Chapter 26 in Financial and Insurance Formulas, 2010, pp 283-305 from Springer

Abstract: Abstract Chapter 26 deals with formulas and laws of probability theory: 26.1. Random Events and Probability, 26.2. Conditional Probability and Independent Events, 26.3. Random Variables and Their Basic Characteristics, 26.4. Important Discrete Distributions, 26.5. Important Continuous Distributions, 26.6. Random Vectors and Their Basic Characteristics, 26.7. Transformation of Random Variables, 26.8. Conditional Mean Value, 26.9. Martingales, 26.10. Generating Function, 26.11. Convolutions and Sums of Random Variables, 26.12. Random Sums of Random Variables, 26.13. Some Inequalities, 26.14. Limit Theorems of Probability Theory.

Keywords: Independent Random Variable; Wiener Process; Negative Binomial Distribution; Moment Generate Function; Discrete Random Variable (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2593-0_26

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DOI: 10.1007/978-3-7908-2593-0_26

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