WorkshopsProjective power entropy and detectability for hidden structures
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We discuss parametric estimation for an exponential family with considerable model uncertainty. For example, the underlying distribution may be k normal mixture distribution even if we assume a normal family. Then the maximum likelihood estimator can suggest only the unique mean; the minimum projective power entropy estimator (MPPE) can properly suggest k means as the local minima. We explore that MPPE satisfies such detectability for hidden structures beyond the model in the light of duality between statistical model and estimation.
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Shinto Eguchi
2011-12-20
13:20:00 - 14:10:00
101 , Mathematics Research Center Building (ori. New Math. Bldg.)
We discuss parametric estimation for an exponential family with considerable model uncertainty. For example, the underlying distribution may be k normal mixture distribution even if we assume a normal family. Then the maximum likelihood estimator can suggest only the unique mean; the minimum projective power entropy estimator (MPPE) can properly suggest k means as the local minima. We explore that MPPE satisfies such detectability for hidden structures beyond the model in the light of duality between statistical model and estimation.