• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.1-9
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• 2009

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, because of the possibility of introducing new faults when correcting or modifying the software, infinite failure non-homogeneous Poisson process models presented and propose an optimal release policies of the life distribution applied fixed shape parameter distribution which can capture the increasing/decreasing nature of the failure occurrence rate per fault. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, make out estimating software optimal release time

• Journal of the Korean earth science society
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• v.21 no.2
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• pp.159-167
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• 2000

We tested the randomness and estimated the degree of concentration for the earthquake occurrence in the Korean Peninsula by using the statistical methods for spatial data. For the randomness test, we applied both of the test statistics based method and the empirical distribution based method to the both of historical and instrumental seismicity data. It was found that the earthquake occurrences for historical and instrumental seismicity data are not random and clustered rather than scattered. A nonparametric density estimation method was used to estimate the concentration degree in the Peninsula. The earthquake occurrences show relatively high concentration on Seoul, Choongnam, Chonbook and Kyungbook areas for the historical seismicity data. Also,'L" shaped concentrations connecting Whanghaedo -the coast of Choongnam -the inland of Kyungbook area are revealed for the instrumental seismicity data.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.477-479
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• 2011

본 논문에서는 1차원 은닉 마코프 모델을 2차원으로 확장하기 위하여 노드들의 마코프 특성이 인과적인 관계를 갖는 마코프 메쉬 모델을 이용하여 완전한 2차원 HMM의 구조를 갖는 모델을 제안한다. 마코프메쉬 모델은 이웃시스템을 통하여 이전의 시점을 정의하고, 인과적인 관계를 통하여 전이확률의 계산을 가능하게 한다. 또한 영상의 최적의 분할을 위하여 계층적 디리슐레 과정을 사전분포로 두어 고정된 상태의 수가 아닌 무한의 상태 수를 갖는 2차원 HMM을 제안한다. HDP로 정의된 사전분포와 관측된 표본 자료의 정보를 갖는 우도함수를 결합한 사후분포의 베이스 추정은 깁스샘플링 알고리즘을 이용하여 계산된다.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.139-148
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• 2014

In recent years, computational models using parametric estimation method have been developed and used widely for efficient cost analysis. In this research, by applying experienced data from Guidance and Control Systems in Missile System field, the cost analysis for engineering model and commercial computational model(Price H, HL, M, S) are conducted and its result is analysed, so that the difference between two models and its grounds are apprehended. Comparing the calibrated value of computational model based on the data base of similar equipment and the cost from the engineering estimation, the two results are very close. It means that the credibility of data is enhanced through calibration. Also, for cost analysis of similar components in the future, the method for calibration of the computational models is also examined. When estimating development cost in this research, although many parts have been estimated through uncertain elements, the reliability could have been enhanced by applying computational model which secures objectivity. It is a very reasonable estimation method by utilizing calibration of the computational models based on existing accumulated development data.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.279-287
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• 2003

In this paper we propose a local smoothing of the Nelson type estimator for the survival function based on an approximation by the Weibull distribution function. It appears that Mean Square Error and Bias of the smoothed estimator of the Nelson type survival function estimators are significantly smaller than that of the smoothed estimator of the Kaplan-Meier survival function estimator.

• 한국데이터정보과학회:학술대회논문집
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• 2003.05a
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• pp.109-119
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• 2003

In this paper we propose a local smoothing of the Nelson type estimator for the survival function based on an approximation by the Weibull distribution function. It appears that Mean Square Error and Bias of the smoothed estimator of the Nelson type survival function estimator is significantly smaller then that of the smoothed estimator of the Kaplan-Meier survival function estimator.

• Journal of Korean Society for Quality Management
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• v.23 no.2
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• pp.91-102
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• 1995

For two independent random variables X and Y, the functional R=Pr[X>Y] is of practical importance in reliability. X can be interpreted as the strength of a component subjected to a stress Y, and R is the component's reliability. In this paper nonparametric approach to estimation of R based on censored observations in the strength variables is analyzed and compared by simulations in the moderate sample sizes.

• Journal of Korean Society for Quality Management
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• v.25 no.4
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• pp.106-114
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• 1997

The smoothing parameter or bandwidth is crucial to performance of the kernel based regression estimator. So the choice of a "optimal" smoothing parameter produce a single curve estimate. If a single estimate is replaced by a family of estimates, it become easy that we understand what varies with choice of the smoothing parameter. This paper suggests the threshold of the maximum bandwidth and the number of the family members in the regression context.n context.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.593-605
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• 2019

Significant literature exists on the area under the ROC curve (AUC) and the volume under the ROC surface (VUS) which are statistical measures of the discriminant power of classification models. Whereas the partial AUC is restricted on the false positive rate, the two-way partial AUC is restricted on both the false positive rate and true positive rate, which could be more efficient and accurate than partial AUC. The two-way partial AUC was suggested as more efficient and accurate than the partial AUC. Partial VUS as well as the three-way partial VUS were also developed for the ROC surface. A proposed AUC is expressed in this paper with probability and integration using two truncated distribution functions restricted on both the false positive rate and true positive rate. It is also found that this AUC has a relation with the two-way partial AUC. The three-way partial VUS for the ROC surface is also related to the VUS using truncated distribution functions. These AUC and VUS are represented and estimated in terms of Mann-Whitney statistics. Their parametric and non-parametric estimation methods are explored based on normal distributions and random samples.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.937-944
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• 2021

The problem of selecting variables is addressed in partial linear regression. Model selection for partial linear models is not easy since it involves nonparametric estimation such as smoothing parameter selection and estimation for linear explanatory variables. In this work, several approaches for variable selection are proposed using a fast forward selection algorithm, least angle regression (LARS). The proposed procedures use t-test, all possible regressions comparisons or stepwise selection process with variables selected by LARS. An example based on real data and a simulation study on the performance of the suggested procedures are presented.