• The Magazine of the IEIE
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• v.31 no.3
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• pp.88-97
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• 2004

최근 통계에 따르면 현재 셀룰러 이동 통신 사용자는 전 세계적으로 수십 억 명에 달하고 있으며, 증가량도 매년 7%에 이른다고 한다. 무선 이동통신은 단순히 편하다는 것 이상의 의미를 지니고 있다. 범지구적인 관점에서 살펴보면 보다 많은 사람들이 무선 기술을 이용하여 인터넷에 접속하려 하고 있다. 따라서 우리가 오늘날 World Wide Web - 스트리밍 서비스, 단문 메시지, 전자상거래, P2P- 을 이용하여 얻는 모든 이득들이 무선으로 확장되고 있는 상황이다.(중략)

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.903-913
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• 2013

Social network services generate a considerable amount of social data every day on personal feelings or thoughts. This social data provides changing patterns of information production and consumption but are also a tool that reflects social phenomenon. We analyze negative emotional words from daily blogs to detect the change in blooger sentiment using multivariate control charts. We used the all the blogs produced between 1 January 2008 and 31 December 2009. Hotelling's T-square control chart control chart is commonly used to monitor multivariate quality characteristics; however, it assumes that quality characteristics follow multivariate normal distribution. The performance of a multivariate control chart is affected by this assumption; consequently, we introduce the support vector data description and its extension (K-control chart) suggested by Sun and Tsung (2003) and they are applied to detect the chage in blogger sentiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.917-928
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• 2010

In this paper, we propose an efficient and adaptive rate control in Frame-layer for H.264/AVC. For given QP, bits according to video characteristics, and current frame is close correlation between the adjacent frames. Using the statistical characteristic, we obtain change of occurrence bit about QP to apply the bit amount by QP from the video characteristic and applied in the estimated bit amount of the each unit of current frame. In addition, we use weight with QP and occurrence bit amount that is statistical information of encoded previous frames. Simulation results show that the proposed rate control scheme could not only achieves time saving of more than 99% over existing rate control algorithm, but also increase the average PSNR of reconstructed video for around 0.02~0.43 dB in all the sequences.

• Korean Journal of Clinical Pharmacy
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• v.20 no.3
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• pp.248-254
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• 2010

본 연구에서는 anthracyclines의 심장 독성을 예방하기 위해 사용되는 dexrazoxane의 가장 적절하고 안전한 용량을 평가하고자 했다. 이 약물은 같은 적응증에도 불구하고 미국과 유럽에서 두 배 차이가 나는 용량으로 허가 받아 사용되고 있다. 그러므로 dexrazoxane의 anthracycline로 인한 심독성의 예방에 관한 논문을 찾아 dexrazoxane : doxorubicin = 20:1의 비율로 사용했을 경우와 10:1로 사용했을 때의 효과와 부작용을 비교하였다. 이 두 가지 용량으로 진행된 모든 임상 연구에서 dexrazoxane이 doxorubicin의 심독성 예방에 통계적으로 유효한 효과가 있다고 결론 내렸다. 또한 dexrazoxane의 추가 요법으로 인해 Tumor effect의 차이를 비교 분석한 결과, 두 가지 용량 모두에서 dexrazoxane이 doxorubicin의 항암 효과에 영향을 미치지 않는 것으로 분석되었다. 대부분의 연구에서 dexrazoxane의 약물 자체의 부작용은 분석하지 않았지만, dexrazoxane:doxorubicin을 20:1의 비율로 사용했던 한 연구에서 dexrazoxane군에서 부작용이 있음이 평가되었다. 반면, dexrazoxane의 용량을 doxorubicin 용량에 비해 10:1로 사용한 모든 연구는, 대상 환자군이 18세 이하의 소아 청소년으로 이 용량을 성인에게도 적용할 수 있는지에 대한 추가 연구가 필요하다. 그러나 항암제의 경우, 대부분 환자의 체표면적(BSA)을 기준으로 약용량을 결정하며, 이는 일반적으로 10세 이상이 되면 어른의 체표면적의 70% 정도가 된다. 그러므로, 본 연구에서는 통계적으로 충분한 수의 10세 이상의 소아, 청소년에게 doxorubicin으로 인한 심독성 예방 효과가 입증되었던 dexrazoxane: doxorubicin을 10:1의 용량으로 사용하여도 임상적인 효과를 기대 할 수 있으며, 이 용량은 dexrazoxane 자체의 유해반응도 감소시킬 수 있을 것이라고 결론 맺는다.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.25-37
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• 2012

Many statistics, such as Cohen's (1960) ${\kappa}$, Scott's (1955) ${\pi}$, and Park and Park's (2007) H have been proposed as measures of agreement to represent inter-rater reliability. This study compared bias, SE, MSE, and CV of the measures of agreement with nominal and ordinal categories in the balanced marginal distributions, and those with nominal categories in the two paradoxical situations. As a result, in all cases, AC1and Hhad smaller SE and CV.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.421-433
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• 1993

Few ovservation can influence in model building procedure and can dominate the least squares fit of a selected model. An observation, however, may not have the same impact on all aspects of regression analysis. We introduce a statistic which measures the impact of individual cases on the overall goodness-of-fit statistics. We also propose an influence measure for variable selection problem. The property of uncorrelatedness between fitted values and residuals has been used to develop the influence measure. The performance of the measures are used to develop the influence measure. The performance of the measures are compared with other widely used influence measures by the analysis of real data.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.99-112
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• 2016

Asymmetric jump-diffusion models are effectively used to model the dynamic behavior of asset prices with abrupt asymmetric upward and downward changes. However, the estimation of their extension to the multivariate asymmetric jump-diffusion model has been hampered by the analytically intractable likelihood function. This article confronts the problem using a data augmentation method and proposes a new Bayesian method for a multivariate asymmetric Laplace jump-diffusion model. Unlike the previous models, the proposed model is rich enough to incorporate all possible correlated jumps as well as mention individual and common jumps. The proposed model and methodology are illustrated with a simulation study and applied to daily returns for the KOSPI, S&P500, and Nikkei225 indices data from January 2005 to September 2015.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.849-858
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• 2016

It is important to control confounding bias when estimating the causal effect of treatment in an observational study. We illustrated that the covariate selection in the causal inference is different from the variable selection in the ANCOVA model. We then investigated the three criteria of covariate selection for controlling confounding bias, which can be used when we have inadequate information to draw a complete causal graph. VanderWeele and Shpitser (2011) proposed one of them and claimed it was better than the other two. We show by example that their criterion also has limitations and some disadvantages. There is no clear winner; however, their criterion is better (if some correction is made on its condition) than the other two because it can remove the confounding bias.

• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.659-669
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• 2021

Multivariate regression often appears in longitudinal or functional data analysis. Since multivariate regression involves multi-dimensional response variables, it is more strongly affected by the so-called curse of dimension that univariate regression. To overcome this issue, Yoo (2018) and Yoo (2019a) proposed three model-based response dimension reduction methodologies. According to various numerical studies in Yoo (2019a), the default method suggested in Yoo (2019a) is least sensitive to the simulated models, but it is not the best one. To release this issue, the paper proposes an selection algorithm by comparing the other two methods with the default one. This approach is called principal selected response reduction. Various simulation studies show that the proposed method provides more accurate estimation results than the default one by Yoo (2019a), and it confirms practical and empirical usefulness of the propose method over the default one by Yoo (2019a).

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.735-744
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• 2021

Maintaining the lifetime of a product is one of the objectives of quality control. In real processes, most samples are constructed with censored data because, in many situations, we cannot measure the lifetime of all samples due to time or cost problems. In this paper, we propose two cumulative sum (CUSUM) control charting procedures to monitor the mean of type I right-censored lognormal lifetime data. One of them is based on the likelihood ratio, and the other is based on the binomial distribution. Through simulations, we evaluate the performance of the two proposed procedures by comparing the average run length (ARL). The overall performance of the likelihood ratio CUSUM chart is better, especially this chart performs better when the censoring rate is low and the shape parameter value is small. Conversely, the binomial CUSUM chart is shown to perform better when the censoring rate is high, the shape parameter value is large, and the change in the mean is small.