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Elements of distribution theory / Thomas A. Severini.

By: Severini, Thomas A. (Thomas Alan), 1959-Material type: TextTextSeries: Cambridge series on statistical and probabilistic mathematicsPublication details: New York, NY : Cambridge University Press, 2005. Description: 1 online resource (xii, 515 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9780511345197; 0511345194; 0511344473; 9780511344473Subject(s): Distribution (Probability theory) | Distribution (Théorie des probabilités) | MATHEMATICS -- Functional Analysis | Distribution (Probability theory)Genre/Form: Electronic books. | Electronic books. Additional physical formats: Print version:: Elements of distribution theory.DDC classification: 515/.782 LOC classification: QA273.6 | .S48 2005ebOnline resources: Click here to access online
Contents:
Cover; Half-title; Series-title; Title; Copyright; Dedication; Contents; Preface; 1 Properties of Probability Distributions; 2 Conditional Distributions and Expectation; 3 Characteristic Functions; 4 Moments and Cumulants; 5 Parametric Families of Distributions; 6 Stochastic Processes; 7 Distribution Theory for Functions of Random Variables; 8 Normal Distribution Theory; 9 Approximation of Integrals; 10 Orthogonal Polynomials; 11 Approximation of Probability Distributions; 12 Central Limit Theorems; 13 Approximations to the Distributions of More General Statistics.
Summary: A detailed non-measure theoretic introduction emphasizing parametric statistical models and other topics useful in understanding statistical methodology.
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Includes bibliographical references (pages 503-505) and indexes.

A detailed non-measure theoretic introduction emphasizing parametric statistical models and other topics useful in understanding statistical methodology.

Cover; Half-title; Series-title; Title; Copyright; Dedication; Contents; Preface; 1 Properties of Probability Distributions; 2 Conditional Distributions and Expectation; 3 Characteristic Functions; 4 Moments and Cumulants; 5 Parametric Families of Distributions; 6 Stochastic Processes; 7 Distribution Theory for Functions of Random Variables; 8 Normal Distribution Theory; 9 Approximation of Integrals; 10 Orthogonal Polynomials; 11 Approximation of Probability Distributions; 12 Central Limit Theorems; 13 Approximations to the Distributions of More General Statistics.

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