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Improved Multivariate Prediction under a General Linear Model

โœ Scribed by C.A. Gotway; N. Cressie

Publisher
Elsevier Science
Year
1993
Tongue
English
Weight
554 KB
Volume
45
Category
Article
ISSN
0047-259X

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โœฆ Synopsis

Assuming a general linear model with known covariance matrix, several linear and nonlinear predictors are presented and their properties are discussed. In the context of simultaneous multiple prediction, a total sum of squared errors is suggested as a loss function for comparing predictors. Based on a fundamental relationship between prediction and estimation, a very general class of predictors is developed from which predictors with uniformly smaller risk than that of the classical best linear unbiased (i.e., universal kriging) predictor can be constructed. r. 199.3 Academic Press, Inc.

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