• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.465-468
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• 2000

본 논문에서는 고장 데이터가 극히 적은 상황에서도 다수의 동일부품이 사용되는 경우에는 중단자료를 활용하여 최우추정법으로 고장수명분포를 추정할 수 있음을 입증한다. 부품의 수명분포로 와이블분포를 사용하며 모수의 최우추정치를 구하는 비교적 단순한 방법을 제시한다. 또한, 향후 주어진 기간동안 필요로 하는 적정 예비품수를 결정하는 확률적 방안을 제안한다 그리고 이와같은 방법을 포항방사광가속기의 주요부품인 광자막이와 수냉플랜지에 적용한 사례를 소개한다.

• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.139-145
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• 2003

본 논문에서는 강수 자료의 예측에 사용되는 3-모수 카파 분포(KD3)에서의 모수 추정 방법을 알아보고 시뮬레이션을 통하여 모수 추정 방법에 따른 성능을 비교해 보았다. 이 분포의 모수 $\alpha,\;\beta,\;\mu$를 추정하기 위하여 적률추정법(MME), L-적률 추정법(LME), 최우추정법(MLE)을 적용하였다. 소표본의 경우뿐만 아니라 대표본의 경우에도 시뮬레이션을 통하여 추정법들의 성능을 비교하였다. 적률 추정법과 L-적률 추정법에서는 제약조건 하에서의 1차원 Newton-Raphson방법을 수정하여 이용하였다. MSE를 기준으로 한 시뮬레이션 결과, KD3의 모수 추정에 있어서 표본의 크기가 100보다 작으면 LME의 적용을 추천하고 표본의 크기가 100이상이면 MLE를 추천한다.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.2053-2061
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• 1994

The static and fatigue tensile tests have been conduted to predict the fatigue life of 8-harness satin woven and plain woven carbon/epoxy composite plates containing a circular hole. A fatigue residual strength degradation model, based on the assumption that the residual strength for unnotched specimen decreases monotonically, has been applied to predict statistically the fatigue life of materials used in this study. To determine the parameters(c, b and K) of the residual strength degradation model, the minimization technique and the maximum likelihood method are used. Agreement of the converted ultimate strength by using the minimization technique with the static ultimate strength is reasonably good. Therefore, the minimization technique is more adjustable in the determination of the parameter and the prediction of the fatigue life than the maximum likelihood method.

• Proceedings of the KSEEG Conference
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• 2007.04a
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• pp.631-633
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• 2007

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.393-399
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• 1993

When we compute the maximum likelihood estimators of the parameters for the logistic regression models, which are useful in studying the relationship between the binary response variable and the explanatory variable, the standard error calculations are usually based on the second derivative of log-likelihood function. On the other hand, an estimator of the Fisher information motivated from the fact that the expectation of the cross-product of the first derivative of the log-likelihood function gives the Fisher information is expected to have similar asymptotic properties. These estimators of Fisher information are closely related with the iterative algorithm to get the maximum likelihood estimator. The average numbers of iterations to achieve the maximum likelihood estimator are compared to find out which method is more efficient, and the estimators of the variance from each method are compared as estimators of the asymptotic variance.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.107-112
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• 2017

This paper performed an experimental study to test the validity of the prospect theory proposed by Tversky and Kahneman as an alternative to the expected utility theory. 115 college students attended the hypothetical games to choose one of two lotteries, one is safe option while the other one is risky. The risky options were set up to have low, medium or high probability of payoffs or losses. The amount of payoffs and losses of the lotteries was either large or small. Maximum likelihood estimation of the hypothetical games have shown that in case of high probability of positive payoffs the respondents were risk averse and when the probability of positive payoffs were small the respondents were risk loving. when the possibility of loss is high they were risk loving, while the probability is of loss is low the respondents were found to be risk averse. When the probability of risky options were medium the results were significant statistically in case of only losses. The amount of positive payoff or losses does not affect the results. Overall the results of this experiments support the prospect theory more than those of Laury & Holts (2008).

• Journal of Digital Convergence
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• v.13 no.12
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• pp.143-149
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• 2015

This study aims to analyze the predict capability of some of the popular software NHPP reliability models(Goel-Okumo model, delayed S-shaped reliability model and Rayleigh distribution model). The predict capability analysis will be on two key factors, one pertaining to the degree of fitment on available failure data and the other for its prediction capability. Estimation of parameters for each model was used maximum likelihood estimation using first 80% of the failure data. Comparison of predict capability of models selected by validating against the last 20% of the available failure data. Through this study, findings can be used as priori information for the administrator to analyze the failure of software.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.35 no.3
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• pp.216-222
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• 2002

Autocorrelation in time series data can affect statistical inference in correlation or regression analyses. To improve a regression model from which the residuals are autocorrelated, Yule-Walker method, nonlinear least squares estimation, maximum likelihood method and 'prewhitening' method have been used to estimate the parameters in a regression equation. This study reviewed on the estimation methods of preventing spurious correlation in the presence of autocorrelation and applied the former three methods, Yule-Walker, nonlinear least squares and maximum likelihood method, to a 20-year real data set. Monte carlo simulation was used to compare the three parameter estimation methods. However, the simulation results showed that the mean squared error distributions from the three methods simulated do not differ significantly.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.463-477
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• 2009

Parameter estimation methods such as maximum likelihood estimation method, probability weighted moments method, regression method have been popularly applied to various extreme value models in numerous literature. Among three methods above, the performance of regression method has not been rigorously investigated yet. In this paper the regression method is compared with the other methods via Monte Carlo simulation studies for estimation of parameters of the Generalized Extreme Value(GEV) distribution and the Generalized Pareto(GP) distribution. Our simulation results indicate that the regression method tends to outperform other methods under small samples by providing smaller biases and root mean square errors for estimation of location parameter of the GEV model. For the scale parameter estimation of the GP model under small samples, the regression method tends to report smaller biases than the other methods. The regression method tends to be superior to other methods for the shape parameter estimation of the GEV model and GP model when the shape parameter is -0.4 under small and moderately large samples.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.35-47
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• 2023

Various single probability distributions have been used to represent time headway distributions. However, it has often been difficult to explain the time headway distribution as a single probability distribution on site. This study used the EM algorithm, which is one of the maximum likelihood estimations, for the parameters of combined mixture distributions with a certain relationship between two normal distributions for the time headway of vehicles. The time headway distribution of vehicle arrival is difficult to represent well with previously known single probability distributions. But as a result of this analysis, it can be represented by estimating the parameters of the mixture probability distribution using the EM algorithm. The result of a goodness-of-fit test was statistically significant at a significance level of 1%, which proves the reliability of parameter estimation of the mixture probability distribution using the EM algorithm.