• 응용통계연구
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• 제15권1호
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• pp.73-84
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• 2002

계수에 대한 부등 제한조건이 있는 선형 회귀모형은 경제모형에서 가장 흔하게 다루어지는 것 중의 하나이다. 이는 특정 설명변수에 대한 계수의 부호를 음양 중 하나로 제한하거나 계수들에 대하여 순서적 관계를 주기 때문이다. 본 논문에서는 이러한 부등 제한이 있는 선형회귀 모형에서 유의한 설명변수의 선택을 해결하는 베이지안 기법을 고려한다. 베이지안 변수선택은 가능한 모든 모형의 사후확률 계산이 요구되는데 본 논문에서는 이러한 사후확률들을 동시에 계산하는 방법을 제시한다. 구체적으로 가장 일반적인 모형의 모수에 대한 사후표본을 깁스 표본기법을 적용시켜 얻은 후 이를 이용하여 모든 가능한 모형의 사후확률을 계산하고 실제적인 자료에 본 논문에서 제안된 방법을 적용시켜 본다.

• 인터넷정보학회논문지
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• 제19권6호
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• pp.101-112
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• 2018

A lot of manpower and budgets are being used to prevent fires, and only a small portion of the data generated during this process is used for disaster prevention activities. This study develops a prediction model of fire occurrence probability based on data mining in order to more actively use these data for disaster prevention activities. For this purpose, variables for predicting fire occurrence probability of various buildings were selected and data of construction administrative system, national fire information system, and Korea Fire Insurance Association were collected and integrated data set was constructed. After appropriate data cleansing and preprocessing, various data mining methodologies such as artificial neural network, decision trees, SVM, and Naive Bayesian were used to develop a prediction model of the fire occurrence probability of buildings. The most accurate model among the derived models is Linear SVM model which shows 68.42% as experimental data and 63.54% as verification data and it is the best model to predict fire occurrence probability of buildings. As this study develops the prediction model which uses only the set values of the specific ranges, future studies may explore more opportunites to use various setting values not shown in this study.

• 한국지반공학회논문집
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• 제19권6호
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• pp.151-160
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• 2003

암반사면의 대표적인 파괴유형인 쐐기파괴에 대한 확률론적 안정 해석 수행 과정에서 가장 주요한 불연속면의 특성인 전단 강도에 대해 Mohr-Coulomb 모델에 의한 선형적 강도특성과 Barton모델에 의한 비선형적 강도특성이 사면의 안정성 해석에 주는 영향을 비교하고자 하였다. 사면 안정성 해석의 방법으로 결정론적 해석과 Monte Carlo Simulation을 이용한 확률론적 해석을 수행하였으며, 불연속면의 통계적 분석을 수행한 후 $x^2$ 검증을 통해 분포함수를 검증하였다. 해석 대상 사면은 중앙선 O O공구로, 불연속면의 특성을 파악하기 위해 BIPS, DOM, Scanline, 절리면 직접전단 시험자료를 사용하였다. Mohr-Coulomb, Barton모델에 의한 결정론적 해석 결과는 모두 안정한 것으로 나타났으나, 확률론적 해석 결과 두 모델 모두 5% 이상의 파괴확률을 나타냄으로서 잠재적인 불안정성을 가지는 것으로 평가되었다. 또한 Mohr-Coulomb의 모델이 Barton의 모델보다 더 큰 파괴확률을 가지는 것으로 나타났다. 불연속면의 전단강도 정수 산정시 Mohr-Coulomb의 모델은 한정된 실내시험 자료를 가지게 되고, 정확한 점착력의 산정이 어려운 점, 파괴블록의 규모가 작은 경우 안전율이 지나치게 과대 평가될 가능성 등이 있으므로, 합리적인 사면 안정성 해석을 위해서는 강도정수 산정시 적절한 모델 선택이 중요하다.

• 한국환경과학회지
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• 제20권12호
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• pp.1541-1551
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• 2011

This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.

• Communications for Statistical Applications and Methods
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• 제10권1호
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• pp.233-237
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• 2003

An asymptotic property of the ordinary least squares estimator of the disturbance variance is considered in the regression model with correlated errors. It is shown that the convergence in probability of S$^2$ is equivalent to the asymptotic unbiasedness. Beyond the assumption on the design matrix or the variance-covariance matrix of disturbances error, the result is quite general and simplify the earlier results.

• Journal of the Korean Statistical Society
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• 제28권3호
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• pp.311-324
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• 1999

The problem of 'outliers', observations which look suspicious in some way, has long been one of the most concern in the statistical structure to experimenters and data analysts. We propose a model for an outlier problem and also analyze it in linear regression model using a Bayesian approach. Then we use the mean-shift model and SSVS(George and McCulloch, 1993)'s idea which is based on the data augmentation method. The advantage of proposed method is to find a subset of data which is most suspicious in the given model by the posterior probability. The MCMC method(Gibbs sampler) can be used to overcome the complicated Bayesian computation. Finally, a proposed method is applied to a simulated data and a real data.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.805-814
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• 2001

The problem of 'outliers', observations which look suspicious in some way, has long been one of the most concern in the statistical structure to experimenters and data analysts. We propose a model for outliers problem and also analyze it in linear regression model using a Bayesian approach with the variance-inflation model. We will use Geweke's(1996) ideas which is based on the data augmentation method for detecting outliers in linear regression model. The advantage of the proposed method is to find a subset of data which is most suspicious in the given model by the posterior probability The sampling based approach can be used to allow the complicated Bayesian computation. Finally, our proposed methodology is applied to a simulated and a real data.

• 전기학회논문지
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• 제61권7호
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• pp.1007-1013
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• 2012

Modeling of photovoltaic power systems is significant to analytically predict its dynamics in practical applications. This paper presents a novel modeling algorithm of such system by using probability and statistic theories. We first establish a linear model basically composed of Fourier parameter sets for mapping the input/output variable of photovoltaic systems. The proposed model includes solar irradiation and ambient temperature of photovoltaic modules as an input vector and the inverter power output is estimated sequentially. We deal with these measurements as random variables and derive a parameter learning algorithm of the model in terms of statistics. Our learning algorithm requires computation of an expectation and joint expectation against solar irradiation and ambient temperature, which are analytically solved from the integral calculus. For testing the proposed modeling algorithm, we utilize realistic measurement data sets obtained from the Seokwang Solar power plant in Youngcheon, Korea. We demonstrate reliability and superiority of the proposed photovoltaic system model by observing error signals between a practical system output and its estimation.

• 한국자동차공학회논문집
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• 제10권4호
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• pp.85-92
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• 2002

To investigate the safety of the in-use vehicles emission against the tail-pipe emission regulation, in-use vehicles emission trend according to vehicle mileage should be known. But it is impossible to collect all vehicles emission data In order to know that. Therefore, it is necessary to establish a statistically meaningful inference method that can be used generally to estimate in-use vehicles emissions distribution according to the vehicle mileage with relatively less in-use vehicles emission data. To do this, a linear regression model that solved the problems of data normality and common variance of error was studied. As a way that can secure the data normality, In(emission) instead of emission itself was used as a sampled data. And a reciprocal of mileage was suggested as a factor to secure common variance of error. As an example, 36 data of FTP-75 test were handled in this study. As a result, using average value and standard deviation at each mileage which were inferred from a linear regression model, probability density distribution and cumulative distribution of emissions according to the vehicle mileage were obtained and it was possible to predict the deterioration factor through full useful life mileage and also possible to decide whether those in-use vehicles will meet the tail-pipe emission regulations or not.

• 대한토목학회논문집
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• 제33권3호
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• pp.1007-1015
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• 2013

하중 발생과정에 따른 누적피해의 선형뿐만 아니라 비선형 거동을 해석할 수 있는 추계학적 확률모형이 수립되었다. 여러 종류의 피해강도함수를 도입하여 내용년수의 파괴확률과 비선형 누적피해의 거동이 자세히 해석되었다. 특히 본 연구에서는 저항한계를 임의의 분포함수를 갖는 확률변수로 취급하여 한계상태의 불확실성을 고려하였다. 또한 피복재에 대한 피해수준을 이용하여 처음으로 추계학적 확률모형을 경사제에 적용하였다. 실험 자료와의 비교를 통해 추정된 경사제 피복재에 대해 피해강도함수를 이용하여 내용년수에 따른 파괴확률과 비선형 누적피해의 거동을 해석하였다. 마지막으로 해석 결과를 이용하여 경사제 피복재의 보수 보강 시점과 최소한의 보수 보강규모를 정량적으로 산정할 수 있는 예방적 유지관리 방법을 제시하였다.