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Diversity is characteristic of the information age and also of
statistics. To date, the social sciences have contributed greatly
to the development of handling data under the rubric of
measurement, while the statistical sciences have made phenomenal
advances in theory and algorithms. Measurement and Multivariate
Analysis promotes an effective interplay between those two realms
of research-diversity with unity. The union and the intersection of
those two areas of interest are reflected in the papers in this
book, drawn from an international conference in Banff, Canada, with
participants from 15 countries. In five major categories - scaling,
structural analysis, statistical inference, algorithms, and data
analysis - readers will find a rich variety of topics of current
interest in the extended statistical community.
These three volumes comprise the proceedings of the US/Japan
Conference, held in honour of Professor H. Akaike, on the Frontiers
of Statistical Modeling: an Informational Approach'. The major
theme of the conference was the implementation of statistical
modeling through an informational approach to complex, real-world
problems. Volume 1 contains papers which deal with the Theory and
Methodology of Time Series Analysis. Volume 1 also contains the
text of the Banquet talk by E. Parzen and the keynote lecture of H.
Akaike. Volume 2 is devoted to the general topic of Multivariate
Statistical Modeling, and Volume 3 contains the papers relating to
Engineering and Scientific Applications. For all scientists whose
work involves statistics.
These three volumes comprise the proceedings of the US/Japan
Conference, held in honour of Professor H. Akaike, on the
`Frontiers of Statistical Modeling: an Informational Approach'. The
major theme of the conference was the implementation of statistical
modeling through an informational approach to complex, real-world
problems. Volume 1 contains papers which deal with the Theory and
Methodology of Time Series Analysis. Volume 1 also contains the
text of the Banquet talk by E. Parzen and the keynote lecture of H.
Akaike. Volume 2 is devoted to the general topic of Multivariate
Statistical Modeling, and Volume 3 contains the papers relating to
Engineering and Scientific Applications. For all scientists whose
work involves statistics.
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."
This volume contains the Proceedings of the Advanced Symposium on
Multivariate Modeling and Data Analysis held at the 64th Annual
Heeting of the Virginia Academy of Sciences (VAS)--American
Statistical Association's Vir ginia Chapter at James Madison
University in Harrisonburg. Virginia during Hay 15-16. 1986. This
symposium was sponsored by financial support from the Center for
Advanced Studies at the University of Virginia to promote new and
modern information-theoretic statist ical modeling procedures and
to blend these new techniques within the classical theory.
Multivariate statistical analysis has come a long way and currently
it is in an evolutionary stage in the era of high-speed computation
and computer technology. The Advanced Symposium was the first to
address the new innovative approaches in multi variate analysis to
develop modern analytical and yet practical procedures to meet the
needs of researchers and the societal need of statistics. vii viii
PREFACE Papers presented at the Symposium by e1l11lJinent
researchers in the field were geared not Just for specialists in
statistics, but an attempt has been made to achieve a well balanced
and uniform coverage of different areas in multi variate modeling
and data analysis. The areas covered included topics in the
analysis of repeated measurements, cluster analysis, discriminant
analysis, canonical cor relations, distribution theory and testing,
bivariate densi ty estimation, factor analysis, principle component
analysis, multidimensional scaling, multivariate linear models,
nonparametric regression, etc."
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."
These three volumes comprise the proceedings of the US/Japan
Conference, held in honour of Professor H. Akaike, on the Frontiers
of Statistical Modeling: an Informational Approach'. The major
theme of the conference was the implementation of statistical
modeling through an informational approach to complex, real-world
problems. Volume 1 contains papers which deal with the Theory and
Methodology of Time Series Analysis. Volume 1 also contains the
text of the Banquet talk by E. Parzen and the keynote lecture of H.
Akaike. Volume 2 is devoted to the general topic of Multivariate
Statistical Modeling, and Volume 3 contains the papers relating to
Engineering and Scientific Applications. For all scientists whose
work involves statistics.
These three volumes comprise the proceedings of the US/Japan
Conference, held in honour of Professor H. Akaike, on the Frontiers
of Statistical Modeling: an Informational Approach'. The major
theme of the conference was the implementation of statistical
modeling through an informational approach to complex, real-world
problems. Volume 1 contains papers which deal with the Theory and
Methodology of Time Series Analysis. Volume 1 also contains the
text of the Banquet talk by E. Parzen and the keynote lecture of H.
Akaike. Volume 2 is devoted to the general topic of Multivariate
Statistical Modeling, and Volume 3 contains the papers relating to
Engineering and Scientific Applications. For all scientists whose
work involves statistics.
This volume contains the Proceedings of the Advanced Symposium on
Multivariate Modeling and Data Analysis held at the 64th Annual
Heeting of the Virginia Academy of Sciences (VAS)--American
Statistical Association's Vir ginia Chapter at James Madison
University in Harrisonburg. Virginia during Hay 15-16. 1986. This
symposium was sponsored by financial support from the Center for
Advanced Studies at the University of Virginia to promote new and
modern information-theoretic statist ical modeling procedures and
to blend these new techniques within the classical theory.
Multivariate statistical analysis has come a long way and currently
it is in an evolutionary stage in the era of high-speed computation
and computer technology. The Advanced Symposium was the first to
address the new innovative approaches in multi variate analysis to
develop modern analytical and yet practical procedures to meet the
needs of researchers and the societal need of statistics. vii viii
PREFACE Papers presented at the Symposium by e1l11lJinent
researchers in the field were geared not Just for specialists in
statistics, but an attempt has been made to achieve a well balanced
and uniform coverage of different areas in multi variate modeling
and data analysis. The areas covered included topics in the
analysis of repeated measurements, cluster analysis, discriminant
analysis, canonical cor relations, distribution theory and testing,
bivariate densi ty estimation, factor analysis, principle component
analysis, multidimensional scaling, multivariate linear models,
nonparametric regression, etc."
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