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Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach - Volume 2 Multivariate Statistical Modeling (Hardcover, 1994 ed.)
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Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach - Volume 2 Multivariate Statistical Modeling (Hardcover, 1994 ed.)
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Often a statistical analysis involves use of a set of alternative
models for the data. A "model-selection criterion" is a formula
which provides a figure-of merit for the alternative models.
Generally the alternative models will involve different numhers of
parameters. Model-selection criteria take into account hoth the
goodness-or-fit of a model and the numher of parameters used to
achieve that fit. 1.1. SETS OF ALTERNATIVE MODELS Thus the focus in
this paper is on data-analytic situations ill which there is
consideration of a set of alternative models. Choice of a suhset of
explanatory variahles in regression, the degree of a polynomial
regression, the number of factors in factor analysis, or the numher
of dusters in duster analysis are examples of such situations. 1.2.
MODEL SELECTION VERSUS HYPOTHESIS TESTING In exploratory data
analysis or in a preliminary phase of inference an approach hased
on model-selection criteria can offer advantages over tests of
hypotheses. The model-selection approach avoids the prohlem of
specifying error rates for the tests. With model selection the
focus can he on simultaneous competition between a hroad dass of
competing models rather than on consideration of a sequence of
simpler and simpler models."
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