Isbn: 9780521785167 - semiparametric regression (cambridge series in statistical and probabilistic mathematics) (cambridge series on statistical and probabilistic mathematics.) (6 Ergebnisse)

Paperback. Zustand: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.

Soft cover. Zustand: Very Good. 1st Edition. Light shelfwear, corners slightly bumped. Binding still tight. All pages intact and free of marks.

Zustand: 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.

Zustand: New. In English.

Zustand: New. This user-friendly 2003 book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. Series Editor(s): Gill, R.; Ripley, Brian D.; Ross, S.; Silverman, B.W. (St Peter's College, Oxford); Stein, M. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 404 pages, 82 b/w illus. BIC Classification: MBNS; PBT. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 252 x 176 x 18. Weight in Grams: 750. . 2003. Illustrated. paperback. . . . . Books ship from the US and Ireland.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that benefits from regression analysis can also benefit from semiparametric regression. Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software. The 2003 book is suitable as a textbook for students with little background in regression as well as a reference book for statistically oriented scientists such as biostatisticians, econometricians, quantitative social scientists, epidemiologists, with a good working knowledge of regression and the desire to begin using more flexible semiparametric models. Even experts on semiparametric regression should find something new here.…