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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."
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.
The pioneering research of Hirotugu Akaike has an international
reputation for profoundly affecting how data and time series are
analyzed and modelled and is highly regarded by the statistical and
technological communities of Japan and the world. His 1974 paper "A
new look at the statistical model identification" (IEEE Trans
Automatic Control, AC-19, 716-723) is one of the most frequently
cited papers in the area of engineering, technology, and applied
sciences (according to a 1981 Citation Classic of the Institute of
Scientific Information). It introduced the broad scientific
community to model identification using the methods of Akaike's
criterion AIC. The AIC method is cited and applied in almost every
area of physical and social science. The best way to learn about
the seminal ideas of pioneering researchers is to read their
original papers. This book reprints 29 papers of Akaike's more than
140 papers. This book of papers by Akaike is a tribute to his
outstanding career and a service to provide students and
researchers with access to Akaike's innovative and influential
ideas and applications. To provide a commentary on the career of
Akaike, the motivations of his ideas, and his many remarkable
honors and prizes, this book reprints "A Conversation with Hirotugu
Akaike" by David F. Findley and Emanuel Parzen, published in 1995
in the journal Statistical Science. This survey of Akaike's career
provides each of us with a role model for how to have an impact on
society by stimulating applied researchers to implement new
statistical methods.
The pioneering research of Hirotugu Akaike has an international
reputation for profoundly affecting how data and time series are
analyzed and modelled and is highly regarded by the statistical and
technological communities of Japan and the world. His 1974 paper "A
new look at the statistical model identification" (IEEE Trans
Automatic Control, AC-19, 716-723) is one of the most frequently
cited papers in the area of engineering, technology, and applied
sciences (according to a 1981 Citation Classic of the Institute of
Scientific Information). It introduced the broad scientific
community to model identification using the methods of Akaike's
criterion AIC. The AIC method is cited and applied in almost every
area of physical and social science. The best way to learn about
the seminal ideas of pioneering researchers is to read their
original papers. This book reprints 29 papers of Akaike's more than
140 papers. This book of papers by Akaike is a tribute to his
outstanding career and a service to provide students and
researchers with access to Akaike's innovative and influential
ideas and applications. To provide a commentary on the career of
Akaike, the motivations of his ideas, and his many remarkable
honors and prizes, this book reprints "A Conversation with Hirotugu
Akaike" by David F. Findley and Emanuel Parzen, published in 1995
in the journal Statistical Science. This survey of Akaike's career
provides each of us with a role model for how to have an impact on
society by stimulating applied researchers to implement new
statistical methods.
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."
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.
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