Isbn: 9781461448174 - essential statistical inference: theory and methods: 120 (13 risultati)

Condizione: 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.

Hardback. Condizione: 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.…

Hardcover. Condizione: 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.

Hardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condizione: New. pp. 588.

Condizione: New. Brand New ! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Valuable text for graduate students and reference for researchersContains R code throughout the text and in sample problems Includes unique page references to equation displaysDennis Boos and Len Stefanski are professors in the Depa.…

Condizione: new. Questo è un articolo print on demand.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware - 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. 588 pp. Englisch.…

Buch. Condizione: Neu. nach der Bestellung gedruckt 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.…

Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿This book is for students and researchers who have had a first year graduate level mathematicalstatistics 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 numberof examples and problems.An important goal has been to make the topics accessible to a wide audience, with little overt relianceon measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimationand 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 forresearch concentrated on measurement error, including a co-authored book on non-linear measurementerror models. In recent years the authors have jointly worked on variable selection methods.¿Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 588 pp. Englisch.…

Condizione: New. Print on Demand pp. 588 34 Illus.

Condizione: New. PRINT ON DEMAND pp. 588.