• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.519-536
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• 1995

In the design of experiments for response surface analysis, sometimes it is of interest to estimate the difference of responses at two points. If differences at points close together are involved, the design that reliably estimates the slope of response surface is important. This idea was conceptualized by slope rotatability by Hader & Park (1978) and Park (1987). Until now, second order polynomial models were only studied for slope ratatability. In this paper, we will propose the necessary and sufficient conditions for slope rotatability over all directions for the thired order polynomial models in two, three and four independent variables. Also practical slope rotatable designs over all directions for two independent variables are suggested.

• The Korean Nurse
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• v.26 no.4 s.142
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• pp.19-25
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• 1987

• Journal of the Korean Mathematical Society
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• v.16 no.2
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• pp.107-111
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• 1980

• Computational Structural Engineering
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• v.25 no.3
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• pp.43-48
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• 2012

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.589-601
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• 2001

Probabilities of overfilling for model selection criteria are derived for several different situations. First, one candidate model with one extra variable is compared to the current model. This is expanded to m candidate models. We show that these comparisons are not independent and discuss ovefitting probabilities. Correlation between two F-tests is derived. Finally, probabilities are computed using the dependent F distributions and F distributions based on order statistics of independent Chi-squares.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.52.5-52
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• 2002

In this paper, we develop analysis models for classification of temporal data from human subjects. The study focuses on the analysis of electroencephalogram (EEG) signals obtained during various emotional states. We demonstrate a generally applicable method of removing EOG and EMG artifacts from EEGs based on independent component analysis (ICA). All EEG channel maps were interpolated from 10 EEG subbands. ICA methods are based on the assumptions that the signals recorded on the scalp are mixtures of signals from independent cerebral and artifactual sources, that potentials arising from different parts of the brain, scalp and body are summed linearly at the electrodes and that prop...

• Journal of Integrative Natural Science
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• v.13 no.1
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• pp.8-12
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• 2020

In this paper we study the Minimum Error Discrimination problem (MED) for ensembles of linearly independent (LI) pure states. By constructing a map from the set on those ensembles we show that the Pretty Good Measurement (PGM) and the optimal measurement for the MED are related by the map.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.485-487
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• 2003

Independent Component Analysis (ICA) is used to generate ICA filter for computing feature vector for image window. Filters that have high discrimination power are selected to classify image from these ICA filters. Proposed classification algorithm is based on probability distribution of feature vector.

• Journal of the Korean Statistical Society
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• v.20 no.1
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• pp.85-92
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• 1991

A set of conditions ensuring local asymptotic normality for independent but not necessarily identically distributed observations in semiparametric models is presented here. The conditions are turned out to be more direct and easier to verify than those of Oosterhoff and van Zwet(1979) in semiparametric models. Examples considered include the simple linear regression model and Cox's proportional hazards model without censoring where the covariates are not random.

• Korean Journal of Radiology
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• v.24 no.11
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• pp.1164-1166
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• 2023