Home Bayesian Methods for Nonlinear Classification and Regression by Denison, David G. T.; Holmes, Christopher C.; Mallick, Bani K.; Smith, Adrian F. M

Bayesian Methods for Nonlinear Classification and Regression by Denison, David G. T.; Holmes, Christopher C.; Mallick, Bani K.; Smith, Adrian F. M

Name: BAYESIAN METHODS FOR NONLINEAR CLASSIFICATION AND REGRESSION
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Author: Denison, D.G.T; Holmes, C.C; Mallick, B.K; Smith, A.F.M
ISBN: 9780471490364

by Denison, David G. T.; Holmes, Christopher C.; Mallick, Bani K.; Smith, Adrian F. M

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Bayesian Methods for Nonlinear Classification and Regression

by Denison, David G. T.; Holmes, Christopher C.; Mallick, Bani K.; Smith, Adrian F. M

Used
good
Hardcover

Wiley. hardcover. Good. 6x0x9.

Bookseller Independent bookstores (US)
Format/Binding Hardcover
Book Condition Used - Good
Quantity Available 1
Binding Hardcover
ISBN 10 0471490369
ISBN 13 9780471490364
Publisher Wiley
Size 6x0x9
X weight 19 oz
Size 6x0x9

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BAYESIAN METHODS FOR NONLINEAR CLASSIFICATION AND REGRESSION

by Denison, D.G.T; Holmes, C.C; Mallick, B.K; Smith, A.F.M

Used
Hardcover
first

Condition

Used

Edition

First Edition

Binding

Hardcover

ISBN 10 / ISBN 13

9780471490364 / 0471490369

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Second Story Books, ABAA

Rockville, Maryland, United States

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New York: Wiley, 2002. First Edition. Hardcover. Octavo, 277 pages. In Very good condition. Blue spine with white lettering. Full binding in blue paper with red details. Boards show mild shelf wear and minor fraying to top corners. Text block clean. Note: Shelved in Netdesk Column F, ND-F. 1378576. FP New Rockville Stock.

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$71.25

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Bayesian Methods for Nonlinear Classification and Regression

by David G. T. Denison

New
Hardcover

Condition

New

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Hardcover

ISBN 10 / ISBN 13

9780471490364 / 0471490369

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Hardback. New. Regression analysis models the relationship between a set of responses and another variable: for example, to estimate the true position of a line through a number of observed points. Unfortunately, data rarely conforms to simple curves and straight lines - parametric models - and this text examines more complex - or nonparametric - models.