• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.443-461
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• 2009

In order to overcome the lack of Korean credit rating migration data, we consider an empirical Bayes procedure to estimate credit rating migration matrices. We derive the posterior probabilities of Korean credit rating transitions by utilizing the Moody's rating migration data and the credit rating assignments from Korean rating agency as prior information and likelihood, respectively. Metrics based upon the average transition probability are developed to characterize the migration matrices and compare our Bayesian migration matrices with some given matrices. Time series data for the metrics show that our Bayesian matrices are stable, while the matrices based on Korean data have large variation in time. The bootstrap tests demonstrate that the results from the three estimation methods are significantly different and the Bayesian matrices are more affected by Korean data than the Moody's data. Finally, Monte Carlo simulations for computing the values of a portfolio and its credit VaRs are performed to compare these migration matrices.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.1-35
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• 2024

The assumption of homoscedasticity is one of the most crucial assumptions for many parametric tests used in the biological sciences. The aim of this paper is to compare the empirical probability of type I error and the power of ten parametric and two non-parametric tests for homoscedasticity with simulations under different types of distributions, number of groups, number of samples per group, variance ratio and significance levels, as well as through empirical data from an agricultural experiment. According to the findings of the simulation study, when there is no violation of the assumption of normality and the groups have equal variances and equal number of samples, the Bhandary-Dai, Cochran's C, Hartley's Fmax, Levene (trimmed mean) and Bartlett tests are considered robust. The Levene (absolute and square deviations) tests show a high probability of type I error in a small number of samples, which increases as the number of groups rises. When data groups display a nonnormal distribution, researchers should utilize the Levene (trimmed mean), O'Brien and Brown-Forsythe tests. On the other hand, if the assumption of normality is not violated but diagnostic plots indicate unequal variances between groups, researchers are advised to use the Bartlett, Z-variance, Bhandary-Dai and Levene (trimmed mean) tests. Assessing the tests being considered, the test that stands out as the most well-rounded choice is the Levene's test (trimmed mean), which provides satisfactory type I error control and relatively high power. According to the findings of the study and for the scenarios considered, the two non-parametric tests are not recommended. In conclusion, it is suggested to initially check for normality and consider the number of samples per group before choosing the most appropriate test for homoscedasticity.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.651-660
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• 2011

This study aims at improving teaching and learning abilities on the courses of probability/statistics in the fields of the S/W and H/W. In order to do this, this paper firstly conducts a survey which measures the perception of the surveyees' necessity of the related courses, and includes the contents that the related courses should cover. Secondly, this paper analyzes the educational effect on the achievement by studying Pattern Recognition, a major course of S/W and H/W, with combining probability/statistics or data analysis. Lastly, this paper suggests the promising pedagogical method for educating probability/statistics by using a survey and the case studies. In this way, this paper shows the necessity of probability/statistics for acquiring a new technology and the flexible approach of various subjects.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.867-872
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• 2005

This study introduces a method to evaluate the probability of a specific area to be affected by a drought of a given severity and shows its potential for investigating agricultural drought characteristics. The method is applied to Gyeonggi as a case study. The proposed procedure includes Standard Precipitation Index(SPI) time series, which are linearly transformed by the Empirical Orthogonal Functions(EOF) method, These EOFs are extended temporally with AutoRegressive Moving Average(ARMA) method and spatially with Kriging method. By performing these simulations, long time series of SPI can be simulated for each designed grid cell in whole Gyeonggi area. The probability distribution functions of the area covered by a drought and the drought severity are then derived and combined to produce drought severity-area-frequency(SAF) curves.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.12
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• pp.1314-1319
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• 2004

The rosen types of piezo-transformers were prepared and electrical properties were investigated in order to establish the optimum parameters in the process of polarization for ferroelectric materials. Polarization was readily originated with increasing the external energy such as an applied voltage, time, and temperature so that the planar coupling factor and voltage gain were saturated under the conditions of over 14$0^{\circ}C$, applied voltage and time of 4 kV/mm and 3 minutes respectively. The empirical equation for domain rotation probability, which was in proportion to square of an applied voltage and temperature and square root of time, as functions of the above parameters was defined.

• Structural Engineering and Mechanics
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• v.28 no.4
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• pp.357-372
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• 2008

This study investigates effect of uncertainty in natural vibration period on the seismic demand. It is shown that since this uncertainty affects the acceleration and displacement responses differently, two ratios, one relating peak acceleration responses and the other relating the peak displacement responses, are not equal and both must be employed in evaluating and defining the critical seismic demand. The evaluation of the ratios is carried out using more than 200 strong ground motion records. The results suggest that the uncertainty in the natural vibration period impacts significantly the statistics of the ratios relating the peak responses. By using the statistics of the ratios, a procedure and sets of empirical equations are developed for estimating the probability consistent seismic demand for both linear and nonlinear systems.

• Ocean and Polar Research
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• v.25 no.spc3
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• pp.347-351
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• 2003

A new approach to reliability analysis of rubble mound breakwater using neural network is proposed. At first, a neural network model which can estimate the stability number of any breakwaters for some design conditions is trained. Then, the neural network model is integrated with Monte Carlo simulation technique in order to calculate probability of failure for the breakwater. The proposed technique is compared with conventional approach using empirical formula.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.47-57
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• 1997

As a general index in surface quality of machined products, surface roughness is to measure worker's skill level, a ground product quality and machining accuracy, etc. The surface roughness is defined by a function of rotational speed and radius of a grinding wheel, distances of active grains composed of the wheel, and feed of a grinder's worktable. To predict surface roughness in horizontal surface grinding operations, probability distributions were used. Probability distribution functions(p.d.f.) of surface roughness were found as results when the size of active grains(=the radius of a grinding wheel) is given as uniform, exponential distribution, and the distance between active grains follows the distributions of uniform, exponential. For each pdf case, probabilistic features of surface roughness were also analyzed and presented. This study is a substantial step for determining mathematically the surface roughness instead of using empirical approaches. More works should be presented to develop a general model by which an accurate roughness value can be obtained in horizontal surface grinding operations.

• KDI Journal of Economic Policy
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• v.38 no.1
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• pp.71-91
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• 2016

This paper examines the effect of the government college loan program in Korea on student academic performance, dropout decisions and loan defaults. While fairness in educational opportunities has been guaranteed to some degree through this program, which started in 2009, there has been a great deal of controversy over its effectiveness. Empirical findings suggest that recipients of general student loan (GSL) lower academic performance than those who received income contingent loan (ICL). Moreover, for students attending private universities, a higher number of loans received increased the probability of a dropout decision, and students from middle-income households had a higher probability of being overdue than students from low-income households. These findings indicate that expanding the ICL program within the allowance of the government budget is necessary. Furthermore, providing opportunities for students to find various jobs and introducing a rating system for defaulters are two necessary tasks.

• KDI Journal of Economic Policy
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• v.43 no.1
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• pp.1-27
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• 2021

In this paper, we empirically examine how export pioneers emerge and how they are related to product creators/innovators, utilizing a rich plant-product level dataset from the Korean manufacturing sector for the period of 1990-1998. Our analysis covers the process from the appearance of product creators as well as product imitators to the emergence of export pioneers. We find, first, that product imitators are larger, more productive and older than product creators. Second, most export pioneers are nevertheless found to be product creators. This result is largely due to the fact that almost all export pioneers export the products in the same year as product creation. Third, there are similarities as well as differences between product creators and export pioneers. Plants that are more productive or larger are more likely to become product creators as well as export pioneers. However, previous exporting experience positively affects the probability of export pioneering only, while plants' engagement in R&D positively affects the probability of product creation only. We discuss possible explanations for our main empirical results as well as their policy implications.