Applied Stochastic Modelling by Morgan Byron (34 results)

Condition: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Paperback. Condition: Good. Derived from a series of talks on aspects of modern statistics for fitting stochastic models to data, commissioned by statisticians at Pfizer Central Research in Sandwich, Kent, UK, Applied Stochastic Modelling, Second Edition presents many of the most important developments and advances in the theory and practice of statistics. Along with coverage of modern techniques, this book integrates and revises standard probability and statistical theory. It also includes over 50 short MATLAB programs as well as S-PLUS versions of these programs, all available from the book's website. This is an ideal textbook and reference source for researchers, undergraduate students, and graduate students in mathematics and statistics.…

Paperback. Condition: Good. Derived from a series of talks on aspects of modern statistics for fitting stochastic models to data, commissioned by statisticians at Pfizer Central Research in Sandwich, Kent, UK, Applied Stochastic Modelling, Second Edition presents many of the most important developments and advances in the theory and practice of statistics. Along with coverage of modern techniques, this book integrates and revises standard probability and statistical theory. It also includes over 50 short MATLAB programs as well as S-PLUS versions of these programs, all available from the book's website. This is an ideal textbook and reference source for researchers, undergraduate students, and graduate students in mathematics and statistics.…

Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Condition: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

N.A. Condition: New. ISBN:9780367414580.

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Paperback. Condition: new. Paperback. Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and improved figures, this edition offers numerous updates throughout. New to the Second Edition An extended discussion on Bayesian methods A large number of new exercises A new appendix on computational methods The book covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. Although the book can be used without reference to computational programs, the author provides the option of using powerful computational tools for stochastic modelling. All of the data sets and MATLAB(R) and R programs found in the text as well as lecture slides and other ancillary material are available for download at Continuing in the bestselling tradition of its predecessor, this textbook remains an excellent resource for teaching students how to fit stochastic models to data. Covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. This work provides the option of using powerful computational tools for stochastic modelling. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Condition: New. In shrink wrap. Looks like an interesting title.

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Condition: New. pp. 368 Index 2nd Edition.

Condition: New. Covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. This work provides the option of using powerful computational tools for stochastic modelling. Series Editor(s): Zidek, James V.; Tanner, Martin Abba; Carlin, Bradley P. Series: Chapman & Hall/CRC Texts in Statistical Science. Num Pages: 368 pages, 73 black & white illustrations. BIC Classification: PBWL. Category: (P) Professional & Vocational. Dimension: 235 x 154 x 19. Weight in Grams: 520. . 2008. 2nd Edition. paperback. . . . .…

Condition: New. pp. 368.

Paperback. Condition: Brand New. 2nd edition. 368 pages. 9.21x5.98x0.71 inches. In Stock.

Condition: New. Covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. This work provides the option of using powerful computational tools for stochastic modelling. Series Editor(s): Zidek, James V.; Tanner, Martin Abba; Carlin, Bradley P. Series: Chapman & Hall/CRC Texts in Statistical Science. Num Pages: 368 pages, 73 black & white illustrations. BIC Classification: PBWL. Category: (P) Professional & Vocational. Dimension: 235 x 154 x 19. Weight in Grams: 520. . 2008. 2nd Edition. paperback. . . . . Books ship from the US and Ireland.…

Condition: New. Byron J.T. MorganHighlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting rea.

Paperback. Condition: new. Paperback. Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and improved figures, this edition offers numerous updates throughout. New to the Second Edition An extended discussion on Bayesian methods A large number of new exercises A new appendix on computational methods The book covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. Although the book can be used without reference to computational programs, the author provides the option of using powerful computational tools for stochastic modelling. All of the data sets and MATLAB(R) and R programs found in the text as well as lecture slides and other ancillary material are available for download at Continuing in the bestselling tradition of its predecessor, this textbook remains an excellent resource for teaching students how to fit stochastic models to data. Covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. This work provides the option of using powerful computational tools for stochastic modelling. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

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Hardcover. Condition: new. Hardcover. Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and improved figures, this edition offers numerous updates throughout. New to the Second Edition An extended discussion on Bayesian methods A large number of new exercises A new appendix on computational methods The book covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. Although the book can be used without reference to computational programs, the author provides the option of using powerful computational tools for stochastic modelling. All of the data sets and MATLAB and R programs found in the text as well as lecture slides and other ancillary material are available for download at Continuing in the bestselling tradition of its predecessor, this textbook remains an excellent resource for teaching students how to fit stochastic models to data. Covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. This work provides the option of using powerful computational tools for stochastic modelling. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Condition: New. 2017. 2nd Edition. hardcover. . . . . .

Condition: New.

Hardcover. Condition: Brand New. 2nd new edition. 368 pages. 10.00x7.01x0.91 inches. In Stock.