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The Linear Model and Hypothesis - A General Unifying Theory (Paperback, Softcover reprint of the original 1st ed. 2015)
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The Linear Model and Hypothesis - A General Unifying Theory (Paperback, Softcover reprint of the original 1st ed. 2015)
Series: Springer Series in Statistics
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This book provides a concise and integrated overview of hypothesis
testing in four important subject areas, namely linear and
nonlinear models, multivariate analysis, and large sample theory.
The approach used is a geometrical one based on the concept of
projections and their associated idempotent matrices, thus largely
avoiding the need to involvematrix ranks. It is shown that all the
hypotheses encountered are either linear or asymptotically linear,
and that all the underlying models used are either exactly or
asymptotically linear normal models. This equivalence can be used,
for example, to extend the concept of orthogonality to other models
in the analysis of variance, and to show that the asymptotic
equivalence of the likelihood ratio, Wald, and Score (Lagrange
Multiplier) hypothesis tests generally applies.
General
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