• Journal of the Korean Data and Information Science Society
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• 제22권6호
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• pp.1265-1273
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• 2011

This article deals with the problem of testing the equality of the location parameters in the half-normal distributions. We propose Bayesian hypothesis testing procedures for the equality of the location parameters under the noninformative prior. The non-informative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to arbitrary constants. This problem can be deal with the use of the fractional Bayes factor or intrinsic Bayes factor. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

• East Asian Economic Review
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• 제18권2호
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• pp.111-142
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• 2014

We examine whether country fundamentals help explain the cross-section of currency excess returns. For this purpose, we consider fundamental variables such as default risk, foreign exchange rate regime, capital control as well as interest rate in the multi-factor model framework. Our empirical results show that fundamental factors explain a large part of the cross-section of currency excess returns. The zero-intercept restriction of the factor model is not rejected for most currencies. They also reveal that our factor model with country fundamentals performs better than a factor model with usual investment-style factors. Our main empirical results are based on 2001-2010 balanced panel data of 19 major currencies. This paper may fill the gap between country fundamentals and practitioners' strategies on currency investment.

• Journal of the Korean Statistical Society
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• 제29권3호
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• pp.337-350
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• 2000

This paper suggests a new diagnostic measure and a stopping rule for detecting influential observations in multiple discriminant analysis (MDA). It is developed from a Bayesian point of view using a default Bayes factor obtained from the fractional Bayes factor methodology. The Bayes factor is taken as a discriminatory information in MDA. It is shown that the effect of an observation over the discriminatory information is fully explained by the diagnostic measure. Based on the measure, we suggest a stopping rule for detecting influential observations in a given training sample. As a tool for interpreting the measure a graphical method is sued. Performance of the method is used. Performance of the method is examined through two illustrative examples.

• Journal of the Korean Data and Information Science Society
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• 제27권3호
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• pp.835-844
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• 2016

We develop the testing procedures about the homogeneity of the shape parameters of several inverse Gaussian distributions in our paper. We propose default Bayesian testing procedures for the shape parameters under the reference priors. The Bayes factor based on the proper priors gives the successful results for Bayesian hypothesis testing. For the case of the lack of information, the noninformative priors such as Jereys' prior or the reference prior can be used. Jereys' prior or the reference prior involves the undefined constants in the computation of the Bayes factors. Therefore under the reference priors, we develop the Bayesian testing procedures with the intrinsic Bayes factors and the fractional Bayes factor. Simulation study for the performance of the developed testing procedures is given, and an example for illustration is given.

• Journal of the Korean Statistical Society
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• 제28권1호
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• pp.73-92
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• 1999

In Bayesian model selection or testing problems, one cannot utilize standard or default noninformative priors, since these priors are typically improper and are defined only up to arbitrary constants. The resulting Bayes factors are not well defined. A recently proposed model selection criterion, the intrinsic Bayes factor overcomes such problems by using a part of the sample as a training sample to get a proper posterior and then use the posterior as the prior for the remaining observations to compute the Bayes factor. Surprisingly, such Bayes factor can also be computed directly from the full sample by some proper priors, namely intrinsic priors. The present paper explains how to derive intrinsic priors for simple tree ordered exponential means. Some numerical results are also provided to support theoretical results and compare with classical methods.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.1295-1299
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• 2008

Soil erosion is a natural process and has been occurring in most areas in the watershed. However, accelerated soil erosion rates have been causing numerous environmental impacts in recent years. To reduce soil erosion and sediment inflow into the water bodies, site-specific soil erosion best management practices (BMPs) need to be established and implemented. The most commonly used soil erosion model is the Universal Soil Loss Equation (USLE), which have been used in many countries over 30 years. The Sediment Assessment Tool for Effective Erosion Control (SATEEC) ArcView GIS system has been developed and enhanced to estimate the soil erosion and sediment yield from the watershed using the USLE input data. In the last decade, the Soil and Water Assessment Tool (SWAT) model also has been widely used to estimate soil erosion and sediment yield at a watershed scale. The SATEEC system estimates the LS factor using the equation suggested by Moore and Burch, while the SWAT model estimates the LS factor based on the relationship between sub watershed average slope and slope length. Thus the SATEEC and SWAT estimated soil erosion values were compared in this study. The differences in LS factor estimation methods in the SATEEC and SWAT caused significant difference in estimated soil erosion. In this study, the difference was -51.9%(default threshold)$\sim$-54.5%(min. threshold) between SATEEC and non-patched SWAT, and -7.8%(default threshold)$\sim$+3.8%(min. threshold) between SATEEC and patched SWAT estimated soil erosion.

• 한국농공학회논문집
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• 제50권1호
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• pp.3-12
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• 2008

Soil erosion is a natural process and has been occurring in most areas in the watershed. However, accelerated soil erosion rates have been causing numerous environmental impacts in recent years. To reduce soil erosion and sediment inflow into the water bodies, site-specific soil erosion best management practices(BMPs) need to be established and implemented. The most commonly used soil erosion model is the Universal Soil Loss Equation(USLE), which have been used in many countries over 30 years. The Sediment Assessment Tool for Effective Erosion Control(SATEEC) ArcView GIS system has been developed and enhanced to estimate the soil erosion and sediment yield trom the watershed using the USLE input data. In the last decade, the Soil and Water Assessment Tool(SWAT) model also has been widely used to estimate soil erosion and sediment yield at a watershed scale. The SATEEC system estimates the LS factor using the equation suggested by Moore and Burch, while the SWAT model estimates the LS factor based on the relationship between sub watershed average slope and slope length. Thus the SATEEC and SWAT estimated soil erosion values were compared in this study. The differences in LS factor estimation methods in the SATEEC and SWAT caused significant difference in estimated soil erosion. In this study, the difference was -51.9%(default threshold)${\sim}-54.5%$(min. threshold) between SATEEC and non-patched SWAT, and -7.8%(default threshold)${\sim}+3.8%$(min. threshold) between SATEEC and patched SWAT estimated soil erosion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3627-3641
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• 2021

Fintech, which stands for financial technology, is growing fast globally since the economic crisis hit the United States in 2008. Fintech companies are striving to secure a competitive advantage over existing financial services by providing efficient financial services utilizing the latest technologies. Fintech companies can be classified into several areas according to their business solutions. Among the Fintech sector, peer-to-peer (P2P) lending companies are leading the domestic Fintech industry. P2P lending is a method of lending funds directly to individuals or businesses without an official financial institution participating as an intermediary in the transaction. The rapid growth of P2P lending companies has now reached a level that threatens secondary financial markets. However, as the growth rate increases, so does the potential risk factor. In addition to government laws to protect and regulate P2P lending, further measures to reduce the risk of P2P lending accidents have yet to keep up with the pace of market growth. Since most P2P lenders do not implement their own credit rating system, they rely on personal credit scores provided by credit rating agencies such as the NICE credit information service in Korea. However, it is hard for P2P lending companies to figure out the intentional loan default of the borrower since most borrowers' credit scores are not excellent. This study analyzed the voices of telephone conversation between the loan consultant and the borrower in order to verify if it is applicable to determine the personal credit score. Experimental results show that the change in pitch frequency and change in voice pitch frequency can be reliably identified, and this difference can be used to predict the loan defaults or use it to determine the underlying default risk. It has also been shown that parameters extracted from sample voice data can be used as a determinant for classifying the level of personal credit ratings.

• Journal of the Korean Data and Information Science Society
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• 제28권1호
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• pp.217-225
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• 2017

This article deals with the problem of multiple hypothesis testing for the shape parameter in the generalized exponential distribution. We propose Bayesian hypothesis testing procedures for multiple hypotheses of the shape parameter with the noninformative prior. The Bayes factor with the noninformative prior is not well defined. The reason is that the most of the noninformative prior can be improper. Therefore we study the default Bayesian multiple hypothesis testing methods using the fractional and intrinsic Bayes factors with the reference priors. Simulation study is performed and an example is given.

• 한국식품과학회지
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• 제37권3호
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• pp.492-497
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• 2005

잔류농약과 관련된 포장시험 및 기준설정에는 데이터의 변이성이 뒤따르기 때문에 여러가지 허수(default value)를 채택하고 있다. 잔류농약 분석상의 오차는 $RSD\;{\pm}30-40%$에 이르고 있어 잔류허용기준(MRL)은 이것을 감안하여 geometric progression에 따르고 있다. 과거 5년간(1998-2002)의 JMPR 보고서에 의하면 포장시험에서의 변이계수(중앙치에 대한 최고치 비율)은 LOQ 이상에서의 486개 농약-작물 조합에서 평균 3.8배에 이르고 있고 기준설정시의 절상효과는 최고치의 1.5배로 나타났다. 한편 국내에서 기준설정시의 규제마진(최고잔류치에 대한 최대잔류기준의 비율)은 822개 농약-작물 조합에서 평균 4.8배로 나타났다. 이와 같은 규제마진을 적용하는 경우 국내의 잔류기준은 Codex보다 높게 설정될 것으로 예상된다. 앞으로 농약잔류 허용기준의 설정에서 Codex기준과 국내기준의 조화를 이루기 위한 검증작업이 이루어져야 할 것이다.