Isbn: 9781461448174 - essential statistical inference: theory and methods (springer texts in statistics, 120, band 120) (4 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Springer, 2013

    1461448174 / 9781461448174

    Serie: Buch 67 von 111 - Springer Texts in Statistics

    • Hardcover

    Anbieter: Wonder Book, Frederick, MD, USAWonder Book

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    EUR 77,94

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    Zustand: Good. Good condition. A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.

  • Sprache: Englisch

    Verlag: Springer-Verlag New York Inc., 2013

    1461448174 / 9781461448174

    Serie: Buch 67 von 111 - Springer Texts in Statistics

    • Hardcover

    Anbieter: World of Books (was SecondSale), Montgomery, IL, USAWorld of Books (was SecondSale)

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    Hardback. Zustand: Good. This book is for students and researchers who have had a first year graduate level mathematical statistics course. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models.…

  • Sprache: Englisch

    Verlag: Springer (edition 2013), 2013

    1461448174 / 9781461448174

    Serie: Buch 67 von 111 - Springer Texts in Statistics

    • Hardcover

    Anbieter: BooksRun, Philadelphia, PA, USABooksRun

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    Zustand: Gebraucht - Ausreichend

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    Hardcover. Zustand: Fair. 2013. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

  • Sprache: Englisch

    Verlag: Springer, 2013

    1461448174 / 9781461448174

    Serie: Buch 67 von 111 - Springer Texts in Statistics

    • Hardcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems.An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology.Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.…