Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach

Bozdogan, H.|Sclove, S. L.|Gupta, Arjun K.|Haughton, D.|Kitagawa, G.|Ozaki, T.|Tanabe, Kunio

ISBN 10: 9401043442 / ISBN 13: 9789401043441

Published by Springer Netherlands, 2012

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Bibliographic Details

• Title: Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach
• Publisher: Springer Netherlands
• Publication Date: 2012
• Language: English
• ISBN 10: 9401043442
• ISBN 13: 9789401043441
• Binding: Soft cover
• Condition: New

About this title

Synopsis

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.