• Communications for Statistical Applications and Methods
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• 제28권4호
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• pp.369-391
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• 2021

The vlda is an R (R Development Core team et al., 2011) package which provides functions for visualization of multidimensional longitudinal data. In particular, the R package vlda was developed to assist in producing a plot that more effectively expresses changes over time for two different types (long format and wide format) and uses a consistent calling scheme for longitudinal data. The main features of this package allow us to identify the relationship between categories and objects using an indicator matrix with object information, as well as to cluster objects. The R package vlda can be used to understand trends in observations over time in addition to identifying relative relationships at a simple visualization level. It also offers a new interactive implementation to perform additional interpretation, therefore it is useful for longitudinal data visual analysis. Due to the synergistic relationship between the existing VLDA plot and interactive features, the user is empowered by a refined observe the visual aspects of the VLDA plot layout. Furthermore, it allows the projection of supplementary information (supplementary objects and variables) that often occurs in longitudinal data of graphs. In this study, practical examples are provided to highlight the implemented methods of real applications.

• 응용통계연구
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• 제3권2호
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• pp.17-25
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• 1990

본 소고에서는 탐색적 데이터분석(EDA)의 방법들이 국내에서 비교적 쉽게 구할 수 있는 통계 팩키지 프로그램에 어떻게 수용되어 있는지를 비교검토할 것이다. 여기에서 고려된 통계 팩키지 프로그램은 IBM-PC의 XT/AT 기종에서 사용가능한 Minitab, NCSS, SAS, SPSS/PC+, Statgraphics, SYSTAT의 모두 6종이다.

• 한국전기전자재료학회논문지
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• 제31권2호
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• pp.122-127
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• 2018

In an attempt to estimate the life projection of LED packages, IESNA published a paper regarding an LED package measurement test method in 2008, and a life projection technical document in 2011, to be used for LED life estimation. IESNA's publications regarding LED package measurement methods were functional, but they were not internationally standardized before 2017. In order to develop a standardized method, the International Standard chose to use the LM-80 as a measurement method for LED life projection in their publication in 2017. Many projection methods have been discussed by the IEC Technical Committee 34 working group, including the method using an exponential function, which reflects lumen degradation characteristics well. This study is designed to explore alternative LED package life estimation methods using an exponential function with statistical analysis, other than the one suggested by the International Standard.

• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.665-674
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• 2015

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

• 응용통계연구
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• 제5권1호
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• pp.93-102
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• 1992

여러 통계 Package에서 사용된 Box Plot Algorithm을 통해 그들을 분석하고 비교하여 최적의 Box Plot Algorithm을 산출하고자 한다.

• 응용통계연구
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• 제26권3호
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• pp.421-429
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• 2013

현대통계학은 많은 분야에서 사용되고 있으나 사용자들이 통계학적 개념을 이해하는데 어려움을 겪고 있다. 한편으로는 초등학생 때부터 줄기잎 그림이나, 비율자료의 원그림 등은 물론이고 평균과 같은 기술통계를 배우고 있다. 초등학교 고학년이나 중학교 저학년 학생들을 위한 직관적인 통계 패키지가 있다면 미래의 통계 사용자들인 이들 학생들이 통계적 개념을 이해하는데 많은 도움이 될 것이라고 생각하여 직관에 기초한 통계 패키지를 개발하였다.

• Journal of the Korean Statistical Society
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• 제6권1호
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• pp.21-24
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• 1977

The cumulants of the sample variance are obtained in terms of the population cumulants using ALMAP (Algebraic Manipulation Package) and these results extend those of Fisher who gave the first six cumulants of the sample variance.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.393-396
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• 2022

• 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.

• 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.