• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.694-702
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• 2014

Since Greenhouse Gas Inventory & Research Center (GIR) of Korea was founded in 2010, the annual greenhouse gas inventory reports, one of the collections of GIR's major affairs, have been published from 2012. In the reports many items related to greenhouse gas emission quantities are included, but among them uncertainty values are replaced to basic values which IPCC guideline suggests. Even though IPCC guideline suggests the equations of each Tier level in details, the guideline recommends developing nation's own methodology on uncertainty which is closely related to statistical problems such as the estimation of a probability density function or Monte carlo methods. In the road transportation sector the emissions have been calculated by Tier 1 but the uncertainties have not been reported. This study introduce a bootstrap technique and Monte carlo method to estimates annual emission quantity and uncertainty, given activity data and emission factors such as annual traveled distances, fuel efficiencies and emission coefficients.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.1
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• pp.34-39
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• 2013

In this study, the quantitative analysis and pattern analysis of the error bounds with respect to recording period were carried out using the wave climate data from coastal areas. Arbitrary recording periods were randomly sampled from one month to six years using the bootstrap method. Based on the analysis, for recording periods less than one year, it was found that the error bounds decreased rapidly as the recording period increased. Meanwhile, the error bounds were found to decrease more slowly for recording periods longer than one year. Assuming the absolute estimate error to be around 10% (${\pm}0.1m$) for an one meter significant wave height condition, the minimum recording period for reaching the estimate error for Sokcho and Geoje-Hongdo stations satisfied this condition with over two years of data, while Anmado station was found to satisfy this condition when using observational data of over three years. The confidence intervals of the significant wave height clearly show an increasing pattern when the percentile value of the wave height increases. Whereas, the confidence intervals of the mean wave period are nearly constant, at around 0.5 seconds except for the tail regions, i.e., 2.5- and 97.5-percentile values. The error bounds for 97.5-percentile values of the wave height necessary for harbor tranquility analysis were found to be 0.75 m, 0.5 m, and 1.2 m in Sokcho, Geoje-Hongdo, and Anmado, respectively.

• KDI Journal of Economic Policy
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• v.26 no.2
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• pp.281-314
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• 2004

This paper theoretically formulated and empirically explored the relationship between exchange rate pass-through (ERPT) for (average) market price and an individual country's price, using steel products data in the US market, with special reference to two major steel exporting countries, Korea and Japan. It was found that the direction of market ERPT can be different from that of individual ERPT that each exporter experiences, due to strategic interactions among producers and different parameters. Vector error correction (VEC) models and impulse response analysis were used with the statistical inference based on the bootstrap-after- bootstrap of Kilian (1998) for short-run, and the fully modified estimation of Phillips and Hansen (1990) was used for long-run. Empirical results indicate that market ERPT in the US market due to changes in Korea-US exchange rates is different from those due to changes in Japan-US exchange rates. The framework developed in this study indicates that this phenomenon is attributed to either (i) the two countries have individual ERPTs of different magnitudes and directions for the products in the US market, or (ii) the pricing strategies of the other exporters' (to the US steel market) respond differently depending on whether the price of the product from Korea changes or that from Japan does. As each exporter's ERPT can be significantly different, and market response to each country's ERPT can be also different, this study concludes that it is crucial for an exporter to understand how competitors in the market respond to changes in its price, as well as to understand how its price changes when the relevant exchange rate fluctuates.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.415-425
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• 2000

We proposed a new classification algorithm based on bootstrap sampling and pairwise coupling method. Also, for comparing the accuracy of a proposed algorithm with those of old methods, we conducted classification with waveform data and others.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.249-265
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• 1995

본 논문에서는 확률분포가 알려져 있지 않은 두 모집단 중 어느 하나로 새로운 관측치를 분류할 때 오분류확률이 분석자에 의해 사전에 정해진 수준에 부합할 수 있도록 커널 판별함수의 임계치를 결정하였다. 정해진 오분류확률을 만족시키기 위한 판별함수의 임계치는 붓스트랩(bootstrap)기법을 판별 함수에 적용시켜 계산된다. 본 논문에서 제시도된 방법은 모집단에 대한 모수적 가정이 없으므로 어느 분포에도 적용가능하며, 모집단이 정규분포, 대수정규분포, 이산형과 연속형 변수가 혼합된 분포의 경우 모의실험을 통하여 그 성능에 대한 검증을 하였다.

• Korean Journal of Environment and Ecology
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• v.17 no.2
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• pp.169-176
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• 2003

The genetic relationships between 4 Korean native Taraxacum and 2 naturalized Taraxacum species were analyzed using the random amplified polymorphic DNA (RAPD) method. Because 141 polymorphic bands were generated from 30 random primers selected through the primer screening, it was possible to analyze the genetic relationship among 6 Taraxacum species. In RAED with the primer OPC12, OPD16, OPK16, OPK17, OPK20, OPS1 or OPS8, many specific polymorphic bands have been appeared in each species. Especially RAPD with the primer OPS8, a specific polymorphic band at 564bp was appeared only in the naturalized Taraxacum officinale. Based on RAPD analysis, Korean native Taraxacum and naturalized Taraxacum species are divided into two groups. T. officinale and T. laevigatum are classified into group I which is a naturalized Taraxacum species group, and T. mongolicum, T. hallasanensis, T. ohwianum and T. coreanum are classified into group II which is a Korean native Taraxacum species group. The result from the RAPD method was very similar to the result from the Bootstrap method. From the examination of the physical characteristics of 6 Taraxacum species populated in Korea, flowering period of Taraxacum species in group I are longer than Taraxacum species in group ll, and the direction of involucral bract of Taruxacum species in the group I was also different comparing to the group ll. Because the flowering color, leaf direction, and the specificity of seed germination of T. coreanum were different compared to the other species in the group II, T. coreanum would be genetically divergent and showed the highest dissimilarity index score.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1718-1724
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• 2017

Recently, Smart plugs for real time monitoring of household appliances based on IoT(Internet of Things) have been activated. Through this, consumers are able to save energy by monitoring real-time energy consumption at all times, and reduce power consumption through alarm function based on consumer setting. In this paper, we measure the alternating current from a wall power outlet for real-time monitoring. At this time, the current pattern for each household appliance was classified and it was experimented with deep learning to determine which product works. As a result, we used a cross validation method and a bootstrap verification method in order to the classification performance according to the type of appliances. Also, it is confirmed that the cost function and the learning success rate are the same as the train data and test data.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.171-180
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• 2016

Basel committee suggests using Value-at-Risk (VaR) and expected shortfall (ES) as a measurement for market risk. Various estimation methods of VaR and ES have been studied in the literature. This paper compares semi-parametric methods, such as conditional autoregressive value at risk (CAViaR) and conditional autoregressive expectile (CARE) methods, and a Gaussian quasi-maximum likelihood estimator (QMLE)-based method through back-testing methods. We use unconditional coverage (UC) and conditional coverage (CC) tests for VaR, and a bootstrap test for ES to check the adequacy. A real data analysis is conducted for S&P 500 index and Hyundai Motor Co. stock price index data sets.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.63-75
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• 2022

This paper proposes the so-called MOSUM-based sparse projection method for change points detection in high-dimensional time series. Our method is inspired by Wang and Samworth (2018), however, our method improves their method in two ways. One is to find change points all at once, so it minimizes sequential error. The other is localized so that more robust to the mean changes offsetting each other. We also propose data-driven threshold selection using block wild bootstrap. A comprehensive simulation study shows that our method performs reasonably well in finite samples. We also illustrate our method to stock prices consisting of S&P 500 index, and found four change points in recent 6 years.