• Journal of Digital Convergence
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• v.16 no.7
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• pp.89-96
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• 2018

In this paper, we proposed a parametric estimation method for estimating H/W cost by using the development data of professional service robot in Korea. In addition, we derived the factors and weights that we can estimate the costs depending on the application environmental conditions of the robot. For the analysis, we developed the equation of professional service robot cost estimation using parametric method. We also derived the adjustment factors and following weights through FGI and Delphi for environmental conditions. We have developed a cost estimation equation that reflects the weight, volume, and manufacturing difficulty, and can derive a relational equation that reflects the environmental factors(dust/water, heat/cold, safety, test, technology innovation). This provides an objective basis for estimating the cost of professional service robots and will lead to ongoing research for estimating the H/W development cost of professional service robots. In the future, we will increase reliability by collecting abundant data, and will strengthen models through finding functional factors.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.365-377
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• 2020

We discuss latent factor regression when constructing a common structure inherent among explanatory variables to solve multicollinearity and use them as regressors to construct a linear model of a response variable. Bayesian estimation with LASSO prior of a large penalty parameter to construct a significant factor loading matrix of intrinsic interests among infinite latent structures. The estimated factor loading matrix with estimated other parameters can be inversely transformed into linear parameters of each explanatory variable and used as prediction models for new observations. We apply the proposed method to Product Service Management data of HBAT and observe that the proposed method constructs the same factors of general common factor analysis for the fixed number of factors. The calculated MSE of predicted values of Bayesian latent factor regression model is also smaller than the common factor regression model.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.51-59
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• 2010

In the case that the regression function has a discontinuity point in generalized linear model, Huh (2009) estimated the location and jump size using the log-likelihood weighted the one-sided kernel function. In this paper, we consider estimation of the unknown number of the discontinuity points in the regression function. The proposed algorithm is based on testing of the existence of a discontinuity point coming from the asymptotic distribution of the estimated jump size described in Huh (2009). The finite sample performance is illustrated by simulated example.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.561-571
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• 2007

Local linear regression estimator is the most widely used nonparametric regression estimator which has a number of advantages over the traditional kernel estimators. It is well known that local linear estimator can produce erratic result in sparse regions in the realization of the design and the interpolation method of Hall and Turlach (1997) is the very efficient way to resolve this problem. However, it has been never pointed out that Hall and Turlach's interpolation method is very sensitive to outliers. In this paper, we propose the robust version of the interpolation method for adapting to sparse design. The finite sample properties of the method is compared with Hall and Turlach's method by the simulation study.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.06a
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• pp.45-56
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• 2001

In this paper, we conducted an empirical study to investigate the design and weighting effects on descriptive and analytic statistics. We compared the regression models using the design-based approach and the generalized estimating equations(GEEs) approach with the model-based approach through the design and weighting effects analysis.

• Proceedings of the Korean Association for Survey Research Conference
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• 2000.06a
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• pp.113-132
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• 2000

본 연구에서 구현하 SLWES(Sampling Learning Web Expert System)은 인터넷 환경에서 표본조사의 학습과 실제 표본조사 자료로부터 모수를 추정할 수 있도록 웹 프로그래밍 기술과 HTML을 결합하여 학습시스템과 통계계산 시스템, 그리고 전문가시스템으로 구성된 표본조사 학습전문가 시스템이다. SLWES는 표본조사에 대하여 전문 지식이 없거나 통계패키지 사용에 익숙하지 않은 비전문가들에게 표본추출법, 무수측정 표본크기 결정 등 표본조사에 대한 이론 학습과 실습의 기회를 인터넷 환경에서 직접 제공함으로써 사용자의 지식에 따라 표본조사론에 대해 체계적이고 효과적으로 학습할 수 있는 시스템이다. 또한 SLWES는 실제 표본조사의 표본추출에 적용될 수 있고 수집된 자료로부터 모수를 추정할수 있으므로 표본조사에 활용될 수 있다.

• Proceedings of the Korean Reliability Society Conference
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• 2006.05a
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• pp.173-180
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• 2006

컨테이너 터미널 장비들은 많은 부품들이 매우 복잡하게 구성되어 있으며, 고장 발생 시에 막대한 비용이 발생하게 된다. 본 연구에서는 컨테이너 터미널 장비의 신뢰도, 가용도, 정비도 향상을 위한 관리 시스템을 개발한다. 개발 시스템은 장비 구성 모듈, 장비 운영 관리 모듈, 정비 관리 모듈, 예비품 관리 모듈, 분석 모듈로 구성되어 있다. 장비의 신뢰도, 가용도, 정비도 향상을 위한 기술로 FMEA, 고장현황 분석, 수명 모수 추정법을 사용한다. 또한 산출된 수명 모수와 객체지향 시뮬레이션 모형으로 최적 예방 정비 주기를 결정하고 이를 이용하여 정비인원과 하루 최대 정비 가능 장비대수를 고려한 연간 최적 예방정비 일정을 결정한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2A
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• pp.197-205
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• 2008

In order to estimate mean wind speed in the Gwangyang-Myodo Region, the probability distribution model of extreme values has been used in the statistical analysis of joint distribution probability of daily maximum wind speed and corresponding direction in this paper. For this purpose frequency of daily maximum records at respective stations is inquired into and sample of largest yearly wind speed of sixteen compass direction and non-direction is extracted from daily data of maximum wind speed and appropriate direction of the meteorological observing stations nearby the bridge construction site. These extreme speed records are applied to Gumbel and Weibull distribution model and parameters are estimated through method of moment and method of least squares etc. And also, distribution and parameters are inquired into whether it is fitted through the probability plot correlation coefficient examination. From fitted parameters the largest yearly wind speed of sixteen compass direction and non-direction is extrapolated taking into account factors regarding sample size of data and distance from the bridge construction site according to the appropriate stations.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.139-151
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• 2002

This study is concerned with model selection and diagnostics for nonlinear regression model through Bayes factor. In this paper, we use informative prior and simulate observations from the posterior distribution via Markov chain Monte Carlo. We propose the Laplace approximation method and apply the Laplace-Metropolis estimator to solve the computational difficulty of Bayes factor.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.123-138
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• 2010

After selecting a group of women with premenstrual syndrome based on daily distress scores of 28 days, one needs to estimate threshold for the change of symptoms, which would be useful for the clinician's diagnosis in hospitals. However, a test of whether a change has occurred has to precede the estimation of the threshold. In this paper, we apply parametric and nonparametric testing methods to an example data obtained from a group of women. Nonparametric method does not assume any distributional form of distress scores and parametric testing method is based on the normal distributions of linear regression lines. Therefore, the optimal situation of both methods would be different and we will assess it with a simulation study.