• Journal of the Korean Data and Information Science Society
• /
• v.18 no.4
• /
• pp.1005-1021
• /
• 2007

Traditional procedures for DNA microarray data analysis are to preprocess and normalize the gene expression data, and then to analyze the normalized data using statistical tests. Drawbacks of the traditional methods are: genuine biological signal may be unwillingly eliminated together with artifacts, the limited number of arrays per gene make statistical tests difficult to use the normality assumption or nonparametric method, and genes are tested independently without consideration of interrelationships among genes. A novel method using average rank in each array is proposed to eliminate such drawbacks. This average rank method monitors differentially regulated genes among genetically different groups and the selected genes are somewhat different from those selected by traditional P-value method. Addition of genes selected by the average rank method to the traditional method will provide better understanding of genetic differences of groups.

• Communications for Statistical Applications and Methods
• /
• v.3 no.3
• /
• pp.113-123
• /
• 1996

Data-dependent (adaptive) choice of asymptotically efficient score functions for rank estimators and M-estimators of regression parameters in a linear regression model with left-truncated and right-censored data are developed herein. The locally adaptive smoothing techniques of Muller and Wang (1990) and Uzunogullari and Wang (1992) provide good estimates of the hazard function h and its derivative h' from left-truncated and right-censored data. However, since we need to estimate h'/h for the asymptotically optimal choice of score functions, the naive estimator, which is just a ratio of estimated h' and h, turns out to have a few drawbacks. An altermative method to overcome these shortcomings and also to speed up the algorithms is developed. In particular, we use a subroutine of the PPR (Projection Pursuit Regression) method coded by Friedman and Stuetzle (1981) to find the nonparametric derivative of log(h) for the problem of estimating h'/h.

• Journal of Korean Society for Quality Management
• /
• v.15 no.2
• /
• pp.50-54
• /
• 1987

A distribution-free rank test for parallelism of regression lines against ordered alternatives is considered. The proposed test statistic is based on the Kepner-Robinson's transformation. The null distribution of the proposed statistic is the same as that of the Wilcoxon signed rank statistic. But, the proposed procedure can be applied only to four or fewer regression lines. The results of a small-sample Monte Carlo study show that the proposed test is comparable with the parametric test in heavy tailed distributions.

• Communications for Statistical Applications and Methods
• /
• v.19 no.3
• /
• pp.367-379
• /
• 2012

In baseball rankings, prediction has been a subject of interest for baseball fans. To predict these rankings, (based on 2011 data from Korea Professional Baseball records) the arithmetic mean method, the weighted average method, principal component analysis, and principal component regression analysis is presented. By standardizing the arithmetic average, the correlation coefficient using the weighted average method, using principal components analysis to predict rankings, the final model was selected as a principal component regression model. By practicing regression analysis with a reduced variable by principal component analysis, we propose a rank predictability model of a pitcher part, a batter part and a pitcher batter part. We can estimate a 2011 rank of pro-baseball by a predicted regression model. By principal component regression analysis, the pitcher part, the other part, the pitcher and the batter part of the ranking prediction model is proposed. The regression model predicts the rankings for 2012.

• Journal of the Korean Home Economics Association
• /
• v.31 no.3
• /
• pp.63-74
• /
• 1993

The purpose of this study is to consider mother's influence in married daughter in family resource management style, and efficiency and the related factors in it. The data were analyzed using frequencies, percentages, Mean, standard deviation, χ2-test, multiple regression analyses and hierachical regression. The following results were acquired: 1) The styles of the mothers' family resource management were in the rank of the seperated, the task-centered, the person-centered and the integrated. According to demographic variables, there was no significant difference, but there was, according to sex-role attitudes. 2) The styles of married daughters' family resource management were in the rank of the separated, the integrated, the person-centered and the task-centered. Among demographic variables, only level of education was significant. 3) Similarity was shown in the mothers' and their married daughters' family resource management styles. 4) The married daughter's efficiency of the management was influenced y accordance of residence, and her own management styles.

• Communications for Statistical Applications and Methods
• /
• v.24 no.2
• /
• pp.115-127
• /
• 2017

This paper proposes a Bayesian test for the equivalence of survival functions in multiple groups. Proposed Bayesian test use the model of Cox's regression with time-varying coefficients. B-spline expansions are used for the time-varying coefficients, and the proposed test use only the partial likelihood, which provides easier computations. Various simulations of the proposed test and typical tests such as log-rank and Fleming and Harrington tests were conducted. This result shows that the proposed test is consistent as data size increase. Specifically, the power of the proposed test is high despite the existence of crossing hazards. The proposed test is based on a Bayesian approach, which is more flexible when used in multiple tests. The proposed test can therefore perform various tests simultaneously. Real data analysis of Larynx Cancer Data was conducted to assess applicability.

• Communications for Statistical Applications and Methods
• /
• v.22 no.5
• /
• pp.415-434
• /
• 2015

In this paper we overview the literature on common features analysis of economic time series. Starting from the seminal contributions by Engle and Kozicki (1993) and Vahid and Engle (1993), we present and discuss the various notions that have been proposed to detect and model common cyclical features in macroeconometrics. In particular, we analyze in details the link between common cyclical features and the reduced-rank regression model. We also illustrate similarities and differences between the common features methodology and other popular types of multivariate time series modelling. Finally, we discuss some recent developments in this area, such as the implications of common features for univariate time series models and the analysis of common autocorrelation in medium-large dimensional systems.

• Communications for Statistical Applications and Methods
• /
• v.10 no.2
• /
• pp.257-266
• /
• 2003

Distribution-free estimation methods are proposed for slope, $\beta$ in the simple linear regression model. In this paper, we suggest the point estimators using the sequential slope based on sign test and Wilcoxon signed rank test. Also confidence intervals are presented for each estimation methods. Monte Carlo simulation study is carried out to compare the efficiency of these methods with least square method and Theil´s method. Some properties for the proposed methods are discussed.

• The Korean Journal of Applied Statistics
• /
• v.19 no.3
• /
• pp.565-578
• /
• 2006

Repeated measurement data between two group is often used in the field of medicine study. In this paper, we suggest a method for comparison of the trend between two groups based on repeated measurement data. First, we estimate regression coefficient of linear regression model from each subject and generate samples using the regression coefficient estimated previous. And then, we test the difference between two groups by unpaired t-test, Wilcoxon rank sum test and placement test using generated samples. Monte Carlo Simulation is adapted to examine the power and experimental significance levels of several methods in various combinations.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.22 no.4
• /
• pp.361-379
• /
• 2011

This paper aims to propose the most appropriate method for calculating the journal PageRank in a domestic citation database. Korean journals show relatively high journal self-citation ratios and have many outgoing citations to external journals which are not included in the domestic citation database. Because the PageRank algorithm requires recursive calculation to converge, those two characteristics of domestic citation databases must be accounted for in order to measure the citation impact of Korean journals. Therefore, two PageRank calculation methods and four formulas for self-citation adjustment have been examined and tested for KSCD journals. The results of the correlation analysis and regression analysis show that the SCImago Journal Rank formula with the cr2 type self-citation adjustment method seems to be a more appropriate way to measure the relative impact of domestic journals in the Korean Science Citation Database.