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  • 1
    Online Resource
    Online Resource
    Cambridge : Cambridge University Press
    UID:
    gbv_883321645
    Format: 1 Online-Ressource (xii, 515 pages) , digital, PDF file(s)
    ISBN: 9780511610547
    Series Statement: Cambridge series on statistical and probabilistic mathematics 17
    Content: This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015)
    Additional Edition: ISBN 9780521844727
    Additional Edition: ISBN 9781107630734
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9780521844727
    Language: English
    Subjects: Mathematics
    RVK:
    Keywords: Wahrscheinlichkeitstheorie ; Wahrscheinlichkeitsverteilung
    URL: Volltext  (lizenzpflichtig)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Cambridge :Cambridge University Press,
    UID:
    almahu_9948233554002882
    Format: 1 online resource (xii, 515 pages) : , digital, PDF file(s).
    ISBN: 9780511610547 (ebook)
    Series Statement: Cambridge series on statistical and probabilistic mathematics ; 17
    Content: This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively.
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015).
    Additional Edition: Print version: ISBN 9780521844727
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    New York, NY :Cambridge University Press,
    UID:
    almafu_9959242710802883
    Format: 1 online resource (xii, 515 pages) : , digital, PDF file(s).
    ISBN: 1-107-15199-6 , 1-281-10852-9 , 9786611108526 , 0-511-34485-6 , 0-511-34447-3 , 0-511-34408-2 , 0-511-56765-0 , 0-511-61054-8 , 0-511-34519-4
    Series Statement: Cambridge series in statistical and probabilistic mathematics
    Content: This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively.
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015). , 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 , 14 Higher-Order Asymptotic ApproximationsAppendix 1 Integration with Respect to a Distribution Function; Appendix 2 Basic Properties of Complex Numbers; Appendix 3 Some Useful Mathematical Facts; References; Name Index; Subject Index , English
    Additional Edition: ISBN 1-107-63073-8
    Additional Edition: ISBN 0-521-84472-X
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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