• Proceedings of the Korean Society of Crop Science Conference
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• 2000.04a
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• pp.282-283
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• 2000

• Proceedings of the Korean Society of Crop Science Conference
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• 2000.04a
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• pp.398-399
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• 2000

• 대한핵의학회:학술대회논문집
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• 2000.05a
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• pp.71.2-71.2
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• 2000

• Proceedings of the Zoological Society Korea Conference
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• 2000.04a
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• pp.85.2-85
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• 2000

No Abstract, See Full Text

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.253-257
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• 2000

A new improved variable structure controller is designed to drive uncertain linear systems to any given point by using a sliding surface with an integral of state error for removing any reaching phases. Predetermination or prediction of output response is feasible for all the persistent disturbances. The usefulness of the proposed algorithm is verified through an illustrative example.

• 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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2000.11a
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• pp.173-174
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• 2000

• Proceedings of the Korean Society of Crop Science Conference
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• 2000.11a
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• pp.171-172
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• 2000

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.23-36
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• 2000

This paper discusses the local influence approach to the Weibull regression model with censored data. Diagnostics for the Weibull regression model are proposed and developed when simultaneous perturbations of the response vector are allowed.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.245-256
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• 2000

Large sample properties of Life-Table estimator are discussed for interval censored bivariate survival data. We restrict out attention to the situation where response times within pairs are not distinguishable and the univariate survival distribution is the same for any individual within any pair.