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Hwang, Changha;Kim, Daehak
- Communications for Statistical Applications and Methods
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- v.4 no.3
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- pp.827-832
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- 1997
Statistical relations between a system and empirical distribution are studied in terms of the concept of Akaike's Information Criterion. From this consideration we derive a bootstrap criterion for determining the optimal number of hidden units in nerual networks.
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Seo, Han-Son
- Communications for Statistical Applications and Methods
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- v.7 no.2
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- pp.393-401
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- 2000
Many graphical methods have been suggested for obtaining an impression of a curvature in regression problem in which some covariates enter nonlinearly. However when true model does not belong to the class of additive models, graphical methods may contain a serious bias. A method is suggested which can avoid such bias in the fitting of nonaddive models.
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Kim, W.C.;Park, B.U.
- Communications for Statistical Applications and Methods
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- v.2 no.2
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- pp.227-230
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- 1995
In this paper, we discuss simple ways of implementing non-basic kernel density estimators which typically ceed extra pilot estimation. The methods utilize order statistics at the pilot estimation stages. We focus mainly on bariable lacation and scale kernel density estimator (Jones, Hu and McKay, 1994), but the same idea can be applied to other methods too.
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Lee, Sunho
- Communications for Statistical Applications and Methods
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- v.7 no.1
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- pp.269-276
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- 2000
there are several methods available for estimating parameters in overdispersed binary response data with the litter effect. Simulations are performed to compare methods for estimating an overall mean and an overdispersion parameter using moments a maximum likelihood under a beta-binomial distribution a maximum quasi-likelihood and a maximum extended quasi-likelihood.
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