• 품질경영학회지
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• 제24권1호
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• pp.87-95
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• 1996

We construct bootstrap confidence bounds for reliability, R=P(X>Y), where X and Y are independent normal random variables. 1-way random effect models with equal variances are assumed for the populations of X and Y. We compare the accuracy of the proposed bootstrap confidence bounds and classical confidence bound for small samples via Monte Carlo simulation.

• Communications for Statistical Applications and Methods
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• 제24권6호
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• pp.641-649
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• 2017

Multivariate confidence regions were defined using a chi-square distribution function under a normal assumption and were represented with ellipse and ellipsoid types of bivariate and trivariate normal distribution functions. In this work, an alternative confidence region using the multivariate quantile vectors is proposed to define the normal distribution as well as any other distributions. These lower and upper bounds could be obtained using quantile vectors, and then the appropriate region between two bounds is referred to as the quantile confidence region. It notes that the upper and lower bounds of the bivariate and trivariate quantile confidence regions are represented as a curve and surface shapes, respectively. The quantile confidence region is obtained for various types of distribution functions that are both symmetric and asymmetric distribution functions. Then, its coverage rate is also calculated and compared. Therefore, we conclude that the quantile confidence region will be useful for the analysis of multivariate data, since it is found to have better coverage rates, even for asymmetric distributions.

• 품질경영학회지
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• 제16권2호
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• pp.10-17
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• 1988

The problem of making confidence statements is considered about the means of treatments with t largest sample values among k available treatments. These confidence bounds are used in selecting a fixed number of superior treatments. An illustrative example is also provided.

• Journal of the Korean Statistical Society
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• 제20권2호
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• pp.108-117
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• 1991

A parametric empirical Bayes procedure is proposed and studied to compare treatments simultaneously with the best. Minimum Bayes risk lower bounds are derived for an additive loss function, and their relationship with Bayesian simultaneous confidence lower bounds is given. For the proposed empirical Bayes procedure, the nominal confidence level both in Bayesian sense and in frequentist's sense is shown to be controlled asymptotically. For practical implementation, a measure of significance similar to f-value is suggested with an illustrative example.

• The Journal of Asian Finance, Economics and Business
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• 제7권8호
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• pp.533-542
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• 2020

This study estimates the nature of the relationship of entrepreneurship and business confidence on youth unemployment in the Philippines over the 2001-2017 period. The paper employed a range of cointegrating regression models, namely, autoregressive distributed lag (ARDL) bounds testing approach, Johansen-Juselius (JJ) and Engle-Granger (EG) cointegration models, dynamic OLS, fully modified OLS, and canonical cointegrating regression (CCR) estimation techniques. The Granger causality based on error correction model (ECM) was also performed to determine the causal link of entrepreneurship and business confidence on youth unemployment. The ARDL bounds testing approach, Johansen-Juselius (JJ) and Engle-Granger (EG) cointegration models confirmed the existence of long-run equilibrium relationship of entrepreneurship and business confidence on youth unemployment. The long-run coefficients from JJ and dynamic OLS show significant long-run and positive relationship of entrepreneurship and business confidence on youth unemployment. While results of the long-run coefficients from fully modified OLS and canonical cointegrating regression (CCR) found that only entrepreneurship has significant and positive relationship with youth unemployment in the long-run. The Granger causality based on error correction model (ECM) estimates show evidence of long-run causal relationship of entrepreneurship and business confidence on youth unemployment. In the short-run, increases in entrepreneurship and business confidence causes youth unemployment to decrease.

• 품질경영학회지
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• 제23권4호
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• pp.64-73
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• 1995

In this paper, the stress strength model is assumed for the populations of X and Y, where distributions of X and Y are independent normal with unknown parameters. We construct bootstrap confidence intervals for reliability, R=P(X>Y) and compare the accuracy of the proposed bootstrap confidence intervals and classical confidence interval through Monte Carlo simulation.

• 한국인터넷방송통신학회논문지
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• 제22권1호
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• pp.77-82
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• 2022

실내공기오염이 인체에 미치는 영향이 실외공기오염보다 더 크며 위험하다. 일반적으로 사람은 실내에 머무는 시간이 길고, 밀폐된 실내는 오염물질이 지속적으로 쌓여 오염된 공기가 폐에 더 잘 전달된다. 특히 어린 아이들의 경우 실내공기에 매우 민감하며 치명적이다. 이와 더불어 코로나19로 인한 더 잦은 실내활동과 지속적으로 증가하는 외부 미세먼지와 함께 환기를 못하는 현재 실내공기오염을 줄이는 방법은 더욱 중요해지고 있다. 본 논문은 기존 자율주행 공기청정 로봇의 문제점을 개선하고자 지도를 분할과 UCT(Upper Confidence bounds applied to Trees) 기반의 알고리즘을 통해 자율주행 로봇이 구역을 살균하지 않거나 한곳에 계속 머무르는 문제점과 실내공기오염에 취약한 아이들의 문제를 개선할 수 있는 그린 스마트 스쿨을 위한 공간 적응형 자율주행 공기청정 로봇을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권2호
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• pp.830-842
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• 2015

Trust and trustworthiness of web services and organizations is calculated as scalar values. But there is still a certain level of risk for the overall reliability of this value. In this article, we focus on calculating trust values as intervals between upper and lower bounds based on predefined confidence values through an additional confidence probability. This will give us a more realistic approach to the trust assessments between individuals and organizations. We also developed a web-based software tool, TAST (Trust Assessment Software Tool) that collects the web services' evaluation of different customer groups for similar organizations through the user interface and calculates the trust intervals for predefined and previously selected confidence values. Our model uses a weighted calculation of mean and variances of customer groups in specific periods and analyses the total and incremental trust of different customer groups.

• International journal of advanced smart convergence
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• 제4권2호
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• pp.46-53
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• 2015

This paper suggests a method of real time confidence interval estimation to detect abnormal states of sensor data. For real time confidence interval estimation, the mean square errors of the exponential smoothing method and moving average method, two of the time series analysis method, were compared, and the moving average method with less errors was applied. When the sensor data passes the bounds of the confidence interval estimation, the administrator is notified through alarms. As the suggested method is for real time anomaly detection in a ship, an Android terminal was adopted for better communication between the wireless sensor network and users. For safe navigation, an administrator can make decisions promptly and accurately upon emergency situation in a ship by referring to the anomaly detection information through real time confidence interval estimation.

• Ocean and Polar Research
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• 제30권2호
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• pp.149-158
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• 2008

The characteristic analysis of the estimated population parameters, i.e., standard deviation and error bound of coastal pollutant concentrations (hereafter PC, i.e., COD, TN, and TP concentrations), was carried out by using environmental data with different sampling frequency in Lake Shihwa and Incheon coastal zone. The results clearly show that standard deviation of the PC increases as its mean value increases. The error bounds of the annual mean values based on seasonally measured DO concentrations and PC data in Incheon coastal zone were estimated as ranges 2.26 mg/l, $0.68{\sim}0.86\;mg/l$, $0.62{\sim}0.80\;mg/l$, and $0.074{\sim}0.082\;mg/l$, respectively. In terms of annual mean of the DO concentration and PC in Lake Shihwa, the error bounds based on monthly measured data from 1997 to 2003 were also estimated as ranges 4.0 mg/l, 3.0 mg/l, $0.5{\sim}1.0\;mg/l$, and 0.05 mg/l, respectively. The error bound on the basis of real-time monitoring data is $7{\sim}13%$ only as compared to that of monthly measured data.