• Journal of the Korean Data and Information Science Society
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• 제10권2호
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• pp.289-298
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• 1999

We consider a minimax approach to make a design robust to many types or uncertainty arising in reality when dealing with non-normal linear models. We try to build a design to protect against the worst case, i.e. to improve the "efficiency" of the worst situation that can happen. In this paper, we especially deal with the generalized linear model. It is a known fact that the generalized linear model is a universal approach, an extension of the normal linear regression model to cover other distributions. Therefore, the optimal design for the generalized linear model has very similar properties as the normal linear model except that it has some special characteristics. Uncertainties regarding the unknown parameters, link function, and the model structure are discussed. We show that the suggested approach is proven to be highly efficient and useful in practice. In the meantime, a computer algorithm is discussed and a conclusion follows.

• Journal of Biosystems Engineering
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• 제41권1호
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• pp.51-59
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• 2016

Purpose: This study examined the performance of two spectroscopy methods and multivariate classification methods to discriminate viable pepper seeds from their non-viable counterparts. Methods: A classification model for viable seeds was developed using partial least square discrimination analysis (PLS-DA) with Fourier transform near-infrared (FT-NIR) and Raman spectroscopic data in the range of $9080-4150cm^{-1}$ (1400-2400 nm) and $1800-970cm^{-1}$, respectively. The datasets were divided into 70% to calibration and 30% to validation. To reduce noise from the spectra and compare the classification results, preprocessing methods, such as mean, maximum, and range normalization, multivariate scattering correction, standard normal variate, and $1^{st}$ and $2^{nd}$ derivatives with the Savitzky-Golay algorithm were used. Results: The classification accuracies for calibration using FT-NIR and Raman spectroscopy were both 99% with first derivative, whereas the validation accuracies were 90.5% with both multivariate scattering correction and standard normal variate, and 96.4% with the raw data (non-preprocessed data). Conclusions: These results indicate that FT-NIR and Raman spectroscopy are valuable tools for a feasible classification and evaluation of viable pepper seeds by providing useful information based on PLS-DA and the threshold value.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.1073-1080
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• 1996

The impact of the input and output probability distributions on the performance of neural networks to forecast two year peak stream flow (cubic meters per second) is examined for two major river basins of the US. The neural network input consisted of drainage area(square kilometers ) and elevation (meters). When data are normally distributed , the neural networks predict much better than when the data are non-normal and have larger tails in their distributions.

• 대한원격탐사학회지
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• 제25권4호
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• pp.321-338
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• 2009

이 연구의 목적은 비대칭 분포를 가지는 현장 조사 자료로부터 GIS 기반 주제도를 생성하기 위한 공간 내삽 방법으로 단변량 크리깅 기법을 비교하는데 있다. 기존 정규 크리깅과 비선형 자료 변환에 기반을 둔 로그 정규 크리깅, 다중 가우시안 크리깅과 지시자 크리깅을 지화학 원소 비소와 납에 대해 사례 연구를 통해 비교하였다. 예측 능력의 비교 분석을 위해 leave-one-out 기반 교차 검증을 통한 오차 분석을 수행하였으며, 샘플링 밀도의 차이에 따른 오차의 변화 양상도 분석하였다. 비교 분석 결과, 지시자 크리깅이 전반적으로 가장 높은 예측 능력을 나타내었으며, 작은 값과 높은 값의 예측 능력도 우수한 것으로 나타났다. 정규 크리깅에 비해 비선형 자료 변환 기반 크리깅 기법들이 우수한 예측 능력을 나타내었지만, 기존에 많이 적용된 로그 정규 크리깅은 샘플링 밀도와 상관없이 편향 정도가 가장 크게 나타내었다. 이 연구를 통해 얻어지는 정량적 검증 결과는 비대칭 분포를 가지는 현장 조사 자료의 내삽을 위한 크기깅 기법의 선정에 유용하게 이용될 수 있을 것으로 기대된다.

• Communications for Statistical Applications and Methods
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• 제30권2호
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• pp.163-178
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• 2023

GARCH-X(1, 1) model specifies that conditional variance follows an AR(1) process and includes a past exogenous variable. This study proposes a new class from that model by allowing a more general (non-linear) variance function to follow an AR(1) process. The functions applied to the variance equation include exponential, Tukey's ladder, and Yeo-Johnson transformations. In the framework of normal and student-t distributions for return errors, the empirical analysis focuses on two stock indices data in developed countries (FTSE100 and SP500) over the daily period from January 2000 to December 2020. This study uses 10-minute realized volatility as the exogenous component. The parameters of considered models are estimated using the adaptive random walk metropolis method in the Monte Carlo Markov chain algorithm and implemented in the Matlab program. The 95% highest posterior density intervals show that the three transformations are significant for the GARCHX(1, 1) model. In general, based on the Akaike information criterion, the GARCH-X(1, 1) model that has return errors with student-t distribution and variance transformed by Tukey's ladder function provides the best data fit. In forecasting value-at-risk with the 95% confidence level, the Christoffersen's independence test suggest that non-linear models is the most suitable for modeling return data, especially model with the Tukey's ladder transformation.

• Nuclear Engineering and Technology
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• 제54권8호
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• pp.2941-2959
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• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

• 한국사회복지학
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• 제68권3호
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• pp.73-103
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• 2016

본 연구는 지적장애 부모를 둔 비장애 청소년들의 삶의 모습과 그들의 삶 속에서 드러난 어려움은 무엇인지 심층적으로 살펴보고, 이에 대한 사회복지적 함의를 제시하고자 한다. 이를 위해 2014년 1월부터 5월까지 청소년 5명을 중심으로 질적 사례연구 방법을 활용하여 사례 내 분석과 사례 간 분석을 하였으며, 연구결과의 신뢰성을 확보하기 위해 매 단계마다 엄격성을 확보하였다. 분석결과는 크게 '비장애 청소년의 성장이야기', '비장애 청소년의 세상살이 이야기'로 분석하였으며, '공부를 하라는 가족이 전혀 없음', '학업 성취감을 알아가며 앞으로 나아감', '나만의 공간으로 숨어버림', '일찍 어른이 되어버림', '다른 부모, 같은 사랑', '가족의 가족이 나를 키움', '나를 그대로 받아들여주는 친구가 있음', '가난한 생활에 짓눌려 살아옴', '힘듦과 힘냄의 양날에 서있음'으로 범주화 하였다. 분 연구결과를 바탕으로 이론적 지평을 넓히고, 가족의 장애이해, 부모역할훈련프로그램과 사례관리 등 실천적 방안을 제시하였으며, 실태조사와 경제적 지원을 위한 수당제도 등 정책적 방안을 함께 제시하였다.

• 한국산업정보학회논문지
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• 제5권3호
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• pp.77-86
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• 2000

The main objectives of this dissertation is to propose a forth generation index C for the case where the target value T is not equal to the midpoint of the specification limits (i.e. asymmetric tolerances), and show that this index is more sensitive compared to the standard PCI's in detacting small shifts of the process mean from the target value. In conclusion, in this dissertation , a new methods for estimating a measure of process capability for non-normally distributed variable data is proposed using the percentage nonconforming.

• Journal of Oral Medicine and Pain
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• 제23권1호
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• pp.65-73
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• 1998

This study evaluated whether substantial airflow resistance changes occurred by changing jaw position in normal and snoring subjects. A case-control design was utilized to assess group differences. Subjects included 11 snoring patients and 10 non-snoring subjects. Airway resistance was assessed using a whole body plethysmograph. Subjects in this study had their mouth opening standardized to a position of 7 mm of vertical separation and the resistance was measured under the following conditions; normal jaw position and 2/3 maximum protrusive jaw position. The results were as follows : 1. The airway resistance was higher in snoring group than in non-snoring group. 2. Both groups had a significant decrease in their airflow resistance upon jaw protrusion. In conclusion, these data document that airflow resistance can be significantly influenced by jaw positioning. Moving the jaw in a protrusive position produced reduction of resistance.

• Communications for Statistical Applications and Methods
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• 제26권3호
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• pp.273-293
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• 2019

We consider the problem of model selection in multiple linear regression with outliers and non-normal error distributions. In this article, the robust model selection criterion is proposed based on the robust estimation method with the least absolute deviation (LAD). The proposed criterion is shown to be consistent. We suggest proposed criterion based algorithms that are suitable for a large number of predictors in the model. These algorithms select only relevant predictor variables with probability one for large sample sizes. An exhaustive simulation study shows that the criterion performs well. However, the proposed criterion is applied to a real data set to examine its applicability. The simulation results show the proficiency of algorithms in the presence of outliers, non-normal distribution, and multicollinearity.