Automatic transaction of signal via statistical modeling |
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Authors: | Genshiro Kitagawa Tomoyuki Higuchi |
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Affiliation: | (1) The Institute of Statistical Mathematics, 4-6-7 Minami-Azabu, Minato-ku, 106-8569 Tokyo, JAPAN |
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Abstract: | The statistical information processing can be characterized by the likelihood function defined by giving an explicit form
for an approximation to the true distribution. This mathematical representation, which is usually called a model, is built
based on not only the current data but also prior knowledge on the object and the objective of the analysis. Akaike2,3) showed that the log-likelihood can be considered as an estimate of the Kullback-Leibler (K-L) information which measures
the similarity between the predictive distribution of the model and the true distribution. Akaike information criterion (AIC)
is an estimate of the K-L information and makes it possible to evaluate and compare the goodness of many models objectively.
In consequence, the minimum AIC procedure allows us to develop automatic modeling and signal extraction procedures. In this
article, we give a simple explanation of statistical modeling based on the AIC and demonstrate four examples of applying the
minimum AIC procedure to an automatic transaction of signals observed in the earth sciences.
Genshiro, Kitagawa, Ph.D.: He is a Professor in the Department of Prediction and Control at the Institute of Statistical Mathematics. He is currently
Deputy Director of the Institute of Statistical Mathematics and Professor of Statistical Science at the Graduate University
for Advanced Study. He obtained his Ph.D. from the Kyushu University in 1983. His primary research interests are in time series
analysis, non-Gaussian nonlinear filtering, and statistical modeling. He has published over 50 research papers. He was awarded
the 2nd Japan Statistical Society Prize in 1997.
Tomoyuki Higuchi, Ph.D.: He is an Associate Professor in the Department of Prediction and Control at the Institute of Statistical Mathematics. He
is currently an Associate Professor of Statistical Science at the Graduate University for Advanced Study. He obtained his
Ph.D. from the University of Tokyo in 1989. His research interests are in statistical modeling of space-time data, stochastic
optimization techniques, and data mining. He has published over 30 research papers. |
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Keywords: | Kullback-Leibler Information Akaike Information Criterion (AIC) Statistical Modeling Signal Processing Generalized State Space Model |
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