• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.291-300
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• 2006

In this research, the performance of widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained empirical Bayes estimator are compared by means of a measurement under balanced loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• 산업경영시스템학회지
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• 제30권3호
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• pp.103-108
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• 2007

This paper presents the conceptual framework for estimating and predicting system's susceptibility to failure as function of condition parameter value which is representing the current status of performance measure using on-line performance reliability. The performance of such system depends on one parameter with a probability distribution that degrades with time gracefully. Performance reliability represents the probability that physical performance will remain satisfactory over a finite period of time or usage cycles in the future. An empirical physical performance function is constructed to incorporate explanatory variables (operating and environmental conditions) over a time or usage dimension. This function enables one to model device performance and the associated classical reliability measures simultaneously, in the performance domain and time domain. The conditional performance reliability structure developed represents a tool to predict system performance over time or usage for next usage period. By enabling such a framework, it can bring us more efficient planning and execution in system's operation control as well as maintenance to reduce costs and/or increase profits.

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.885-898
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• 2012

In this paper, we consider Bayesian approaches to partially linear models, in which a regression function is represented by a semiparametric additive form of a parametric linear regression function and a nonparametric regression function. We make a comparative study on the performance of widely used Bayesian partially linear models in terms of empirical analysis. Specifically, we deal with three Bayesian methods to estimate the nonparametric regression function, one method using Fourier series representation, the other method based on Gaussian process regression approach, and the third method based on the smoothness of the function and differencing. We compare the numerical performance of three methods by the root mean squared error(RMSE). For empirical analysis, we consider synthetic data with simulation studies and real data application by fitting each of them with three Bayesian methods and comparing the RMSEs.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.371-382
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• 2005

The paper compares the performance of some widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained Bayes estimator by means of a new measurement under squared error loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• 재무관리연구
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• 제26권1호
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• pp.31-64
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• 2009

이 논문은 한국의 주식형 펀드에 대한 실증 분석을 통해서, 펀드 판매사의 역할과 판매 보수의 적정성을 평가하였다. 분석 결과는 다음과 같이 요약된다. 첫째, 판매 보수가 높은 펀드가 우월한 운용성과를 보여주지는 않았으며, 오히려 높은 판매 보수가 운용성과를 하락시키는 요인으로 작용하였다. 둘째, 은행과 증권사가 판매사로서 운용성과의 제고에 기여했다는 것은 확인할 수 없었다. 특히, 판매사 중에서 은행은 증권사에 비하여 높은 펀드 보수를 부과함으로써 운용성과에 부정적인 영향을 주었던 것으로 판단된다. 본 연구의 분석 결과는 판매사의 보수가 상대적으로 높이 책정되어 있다는 인식이 전혀 근거가 없는 것은 아니며, 투자자에 대한 편익 제공이라는 측면에서 합리적인 펀드 보수 체계의 확립이 필요하다는 점을 시사한다.

• 한국의류학회지
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• 제22권3호
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• pp.374-383
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• 1998

Apparel Quality was one of the most important elements to evaluate the reputations of companies and products which affect the consumer's purchasing behavior. From researches on apparel quality, there was no common concept of quality as well as no common dimensions. The purposes of this study were to identify apparel quality concept and to classify the multi-dimensional concept of apparel quality. The research was carried out in theoretical as well as empirical studies. The theoretical study was conducted to find out apparel quality concept and divide apparel quality concept into four dimensions groups. The empirical study followed the theoretical study to confirm the multi-dimensional concept of apparel quality. The empirical study was investigated that the questionnaire was administered to 634 housewives in Seoul, Kwangju, and Busan during the fall of 1996. The data were analysed by LISREL analysis. This study identified that apparel quality was characteristics of consumer's desires for apparel. The results of the theoretical study verified that apparel quality concept was organized into four different dimensions: physical attribute, physical function, instrumental performance, and expressive performance.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.195-203
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• 2007

In this paper we propose support vector quantile regression (SVQR) for randomly right censored data. The proposed procedure basically utilizes iterative method based on the empirical distribution functions of the censored times and the sample quantiles of the observed variables, and applies support vector regression for the estimation of the quantile function. Experimental results we then presented to indicate the performance of the proposed procedure.

• Communications for Statistical Applications and Methods
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• 제21권2호
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• pp.125-134
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• 2014

Kullback-Leibler (KL) information is a measure of discrepancy between two probability density functions. However, several nonparametric density function estimators have been considered in estimating KL information because KL information is not well-defined on the empirical distribution function. In this paper, we consider the KL information of the equilibrium distribution function, which is well defined on the empirical distribution function (EDF), and propose an EDF-based goodness of fit test statistic. We evaluate the performance of the proposed test statistic for an exponential distribution with Monte Carlo simulation. We also extend the discussion to the censored case.

• ETRI Journal
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• 제38권4호
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• pp.634-644
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• 2016

Channel-based radio-frequency fingerprinting such as a channel impulse response (CIR), channel transfer function (CTF), and frequency coherence function (FCF) have been recently proposed to improve the accuracy at the physical layer; however, their empirical performance, advantages, and limitations have not been well reported. This paper provides a comprehensive empirical performance evaluation of RF location fingerprinting, focusing on a comparison of received-signal strength, CIR-, CTF-, and FCF-based fingerprinting using the weighted k-nearest neighbor pattern recognition technique. Frequency domain channel measurements in the IEEE 802.11 band taken on a university campus were used to evaluate the accuracy of the fingerprinting types and their robustness to human-induced motion perturbations of the channel. The localization performance was analyzed, and the results are described using the spatial and temporal radio propagation characteristics. In particular, we introduce the coherence region to explain the spatial properties and investigate the impact of the Doppler spread in time-varying channels on the time coherence of RF fingerprint structures.

• Communications for Statistical Applications and Methods
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• 제21권3호
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• pp.261-274
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• 2014

In this paper we develop Bayes and empirical Bayes estimators of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation under the balanced loss function. We compare the performance of the optimal Bayes estimator with ones of the classical sample mean and the usual Bayes estimator under the squared error loss with respect to the posterior expected losses, risks and Bayes risks when the underlying distribution is normal as well as when they are binomial and Poisson.