Optimal Discriminant Analysis : Linear Discriminant Analysis, Analysis of Variance, Regression Analysis, Dependent Variable

Language: English

Published by Omniscriptum, 2010

6130499663 / 9786130499662

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nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! Optimal discriminant analysis (ODA) and the related classification tree analysis (CTA) are statistical methods that maximize predictive accuracy. For any specific sample and exploratory or confirmatory hypothesis, optimal discriminant analysis (ODA) identifies the statistical model that yields maximum predictive accuracy, assesses the exact Type I error rate, and evaluates potential cross-generalizability. Optimal discriminant analysis may be applied to 0 dimensions, with the one-dimensional case being referred to as UniODA and the multidimensional case being referred to as MultiODA. Classification tree analysis is a generalization of Optimal Discriminant Analysis to non-orthogonal trees. Optimal Discriminant Analysis and Classification Tree Analysis may be used to find the combination of variables and cut points that best separate classes of objects or events. These variables and cut points may then be used to reduce dimensions and to then build a statistical model that optimally describes the data.

Seller Inventory # 9786130499662

Title
Optimal Discriminant Analysis : Linear Discriminant Analysis, Analysis of Variance, Regression Analysis, Dependent Variable
Author
Miriam T. Timpledon
Publisher
Omniscriptum
Publication year
2010
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6130499663
ISBN 13
9786130499662
Item weight
143 grams
Dimensions
220x150x6 mm

AHA-BUCH GmbH

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