• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.179-189
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• 2024

In multivariate regression with a high-dimensional response Y ∈ ℝ^r and a relatively low-dimensional predictor X ∈ ℝ^p (where r ≥ 2), the statistical analysis of such data presents significant challenges due to the exponential increase in the number of parameters as the dimension of the response grows. Most existing dimension reduction techniques primarily focus on reducing the dimension of the predictors (X), not the dimension of the response variable (Y). Yoo and Cook (2008) introduced a response dimension reduction method that preserves information about the conditional mean E(Y | X). Building upon this foundational work, Yoo (2018) proposed two semi-parametric methods, principal response reduction (PRR) and principal fitted response reduction (PFRR), then expanded these methods to unstructured principal fitted response reduction (UPFRR) (Yoo, 2019). This paper reviews these four response dimension reduction methodologies mentioned above. In addition, it introduces the implementation of the mbrdr package in R. The mbrdr is a unique tool in the R community, as it is specifically designed for response dimension reduction, setting it apart from existing dimension reduction packages that focus solely on predictors.

• 한국마이크로전자및패키징학회:학술대회논문집
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• 한국마이크로전자및패키징학회 2001년도 추계 기술심포지움
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• pp.119-123
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• 2001

In this paper, a new structure and fabrication method for the wafer level package(WLP) is presented. A packaged VLSI chip is encapsulated by a parylene(which is a low k material) layer as a dielectric layer and is molded by SUB photo-epoxy with dielectric constant of 3.0 at 100 MHz. The electrical parameters (R, L, C) of package traces are extracted by using the Maxwell 3-D simulator. Based on HSPICE simulation results, the proposed wafer level package can operate for frequencies up to 20GHz.

• 한국마이크로전자및패키징학회:학술대회논문집
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• 한국마이크로전자및패키징학회 2000년도 Proceedings of 5th International Joint Symposium on Microeletronics and Packaging
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• pp.3-7
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• 2000

In summary, a fundamentally new paradigm called System-on-Package could potentially become a complementary alternative to System-on-Chip, thus providing a balanced set of system-level functions between the semiconductor IC and single component package beyond the year 2007. The concurrent engineering and optimization of IC and package could overcome the fundamental IC issues presented above.

• 지식경영연구
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• 제20권2호
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• pp.1-24
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• 2019

This tutorial introduces procedures and methods for performing structural equation modeling using R. To do this, we present advanced analysis methods based on structural equation model such as mediation effect analysis, moderation effect analysis, moderated mediation effect analysis, and multiple-group analysis with R program code using R lavaan package that supports structural equation modeling. R is flexible and scalable, unlike traditional commercial statistical packages. Therefore, new analytical techniques are likely to be implemented ahead of any other statistical package. From this point of view, R will be a very appropriate choice for applying new analytical techniques or advanced techniques that researchers need. Considering that various studies in the social sciences are applying structural equations modeling techniques and increasing interest in open source R, this tutorial is expected to be useful for researchers who are looking for alternatives to existing commercial statistical packages.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.931-940
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• 2013

For analysis of clustered survival data, the inferences of parameters in semi-parametric frailty models have been widely studied. It is also important to investigate the potential heterogeneity in event times among clusters (e.g. centers, patients). For purpose of this analysis, the interval estimation of frailty is useful. In this paper we propose a visualizing method to present confidence intervals of individual frailties across clusters using the frailtyHL R-package, which is implemented from h-likelihood methods for frailty models. The proposed method is demonstrated using two practical examples.

• 지구물리와물리탐사
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• 제11권4호
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• pp.379-384
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• 2008

R언어는 통계적 계산과 그래픽을 위한 무료 소프트웨어로 유닉스 뿐 아니라 MS 윈도우상에서도 잘 구동되며, 명령어가 이해하기 쉽고 명령에 대한 Help 기능이 컴퓨터상에서 대화형으로 잘 구비되어 있다. 수많은 패키지에 의해 여러 분야에서 활용되고 있는데, 'RSEIS' 패키지를 사용하면 그래픽에 의한 지진자료처리 작업이 매우 수월하여 그 예를 소개한다.

• 한국전자통신학회논문지
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• 제9권8호
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• pp.883-888
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• 2014

시뮬레이션은 현대의 복잡한 환경에서 효율적인 의사 결정을 위한 도구로서 폭넓게 사용되고 있다. 하지만, 대부분은 결과의 분석 보다는 시뮬레이션 모델의 개발 및 수행에 중점을 두고 있다. 본 논문에서는 시뮬레이션 모델링은 물론 결과의 분석도 중요하고 체계적으로 진행되어야 한다는 점을 강조하고, 이를 위하여 통계분석과 다양한 데이터 조작 및 그래픽 기능을 가진 R을 사용하여 이윤 최적화 시뮬레이션에 대한 모델링과 결과 데이터의 조작 및 다양한 그래픽을 사용한 분석 작업을 수행하여 유용성을 입증하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.177-182
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• 2004

Electronic products are subjected to many different types of shock environment. As the Optical Disc Drive (ODD) market grows, the number of failures related to shock increases. Therefore, it is necessary to improve the performance of cushion package as well as the product design. Cushion materials such as expanded polystyrene are often used to protect electronic products from shock environment. In this paper, the drop analysis of the cushion package f3r optical disc drives was carried out with the explicit method of LS-DYNA and verified by the drop test. For the optimization of package, response surface approximation model was created using central composite design. As a result, cushioning performance was improved under the critical condition and practical design guidelines of cushion package were suggested.

• Journal of the Korean Data and Information Science Society
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• 제28권5호
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• pp.1001-1019
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• 2017

신호 처리는 전자 공학의 한 분야로서 시계열 분석과 매우 깊은 연관성을 갖고 있다. 신호 처리를 위해 현재는 상용 프로그램이 널리 사용되고 있는데 적지 않은 비용을 지불해야 한다. 반면 통계 분석을 위해서는 R이라는 무상 프로그램이 널리 사용되고 있다. 본 연구에서는 신호 처리를 위한 R-프로그램 활용서를 만들어 보았다. 본 연구의 구성은 신호 처리에 대한 이론을 간단히 정리하고 적당한 예제들을 택하여 R을 활용하여 구현하는 방식으로 되어있다. 각 단원에 서술 된 이론을 읽고 해당하는 그림과 R 코드를 제 8장에서 찾아서 구현해보는 방법으로 본 활용서를 사용할 수 있겠다. 연구의 순서는 (1). 푸리에 변환과 역변환 (2). 스펙트럼분석 (3). 비모수적 주기도와 모수적 주기도 (4). 필터의 구성과 소음처리 순서로 되어있다. 본 활용서는 신호 처리를 완벽하게 이해하기에는 분명 부족하지만 처음 시작하는 단계로서 도움이 됐으면 한다.

• Communications for Statistical Applications and Methods
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• 제18권3호
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• pp.319-331
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• 2011

In this paper, we propose automatic procedures for the model selection of various univariate time series data. Automatic model selection is important, especially in data mining with large number of time series, for example, the number (in thousands) of signals accessing a web server during a specific time period. Several methods have been proposed for automatic model selection of time series. However, most existing methods focus on linear time series models such as exponential smoothing and autoregressive integrated moving average(ARIMA) models. The key feature that distinguishes the proposed procedures from previous approaches is that the former can be used for both linear time series models and nonlinear time series models such as threshold autoregressive(TAR) models and autoregressive moving average-generalized autoregressive conditional heteroscedasticity(ARMA-GARCH) models. The proposed methods select a model from among the various models in the prediction error sense. We also provide an R package autots that implements the proposed automatic model selection procedures. In this paper, we illustrate these algorithms with the artificial and real data, and describe the implementation of the autots package for R.