• Title/Summary/Keyword: test statistics

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Testing Procedure for Scale Shift at an Unknown Time Point

  • Song, Il-Seong
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.21-27
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    • 1996
  • A testing procedure is considered to the problem of testing whether there exists a shift in scale at an unknown time point whem a fixed number of observations are drawn successively in time. A test statistic based on squared ranks test for equal variances is suggested and its aymptotic distrbution is dereived. Small sample power comparisons are performed.

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Robustness of Bayes Test on Dependent Sample

  • Oh, Hyun-Sook
    • Communications for Statistical Applications and Methods
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    • v.4 no.3
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    • pp.787-793
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    • 1997
  • It is well known that the assumption of independence is ofter not valid for real data. This phenomenon has been observed empirically by many prominent scientists. In this article the sensitivity of dependence on Bayes test of a sharp null hypothesis is considered. The robustness is considered with respect to the significant level and the prior probability on the null hypothesis.

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Asymptotic Properties of Outlier Tests in Nonlinear Regression

  • Kahng, Myung-Wook
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.205-211
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    • 2006
  • For a linear regression model, the necessary and sufficient condition for the asymptotic consistency of the outlier test statistic is known. An analogous condition for the nonlinear regression model is considered in this paper.

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Test of Homogeneity for a Panel of Seasonal Autoregressive Processes

  • Lee, Sung-Duck
    • Journal of the Korean Statistical Society
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    • v.22 no.1
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    • pp.125-132
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    • 1993
  • Large sample test of homogeneity for a panel of more than two seasonal autoregressive processes is derived and its limiting distribution is found. Detailed results are shown for the important special case that the seasonal and nonseasonal autoregressive components are both of order one.

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Testing for Grouped Heteroscedasticity in Linear Regression Model

  • Song, Seuck Heun;Choi, Moon Kyung
    • Communications for Statistical Applications and Methods
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    • v.11 no.3
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    • pp.475-484
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    • 2004
  • This paper consider the testing problem of grouped heteroscedasticity in the linear regression model. We provide the Lagrange Multiplier(LM), Wald, Likelihood Ratio (LR) test statistis for testing of grouped heteroscedasticity. Monte Carlo experiments are conducted to study the performance of these tests.

A default-rate comparison of the construction and other industries using survival analysis method (생존분석기법을 이용한 건설업과 타 업종간의 부도율 비교 분석)

  • Park, Jin-Kyung;Oh, Kwang-Ho;Kim, Min-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.4
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    • pp.747-756
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    • 2010
  • With the recent recession, studies on the economy are actively being conducted throughout the industry. Based on the Small Business data registered in the Credit Guarantee Fund, we estimated the survival probability in the context of the survival analysis. We also analyzed the survival time for the construction and the other industries which are distinguished depending on the types of business and assets in the Small Business. The survival probability was estimated by using the life-table and the difference between the survival probabilities for the different types of business was described via the method of the Log-rank test and the Wilcoxon test. We found that the small business with over one billion asset has the highest survival probability and that with less than 1000 million asset showed the similar survival probability. In terms of types of business Wholesale and Retail trade industry and Services were relatively high in the survival probability than Light, Heavy, and the construction industries. Especially the construction industry showed the lowest survival probability. Most of the Small Business tend to increase in the hazard rate over time.

The Convergence Influence of Clinical Performance Ability, Clinical Practice Satisfaction, and Emotional Intelligence on Nursing Professionalism of Nursing Students (간호대학생의 임상수행능력, 임상실습 만족도 및 감성지능이 간호전문직관에 미치는 융복합적 영향)

  • Kim, Ga-Ya
    • Journal of Convergence for Information Technology
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    • v.12 no.2
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    • pp.63-71
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    • 2022
  • The purpose of this study is a descriptive research study to understand to investigate the convergence effects of nursing students clinical performance ability, clinical practice satisfaction, and emotional intelligence on nursing professionalism. From November 10 to November 20, 2021, 132 fourth-year nursing students 132 students in 4th year nursing department were surveyed using a convenience sampling. The collected data were analyzed using descriptive statistics, t-test and ANOVA, Scheff'e test, Pearson correlation coefficient, and multiple regression analysis using SPSS Statistics 25.0. As a result of the study, factors affecting nursing professionalism were emotional intelligence(β=.46, p<.001), clinical performance (β=.18, p=.033), and clinical practice satisfaction(β=.18, p=.027) and the explanatory power of nursing professionals was 52%. Therefore, it is expected that it will be used as basic data for a program that can improve professional nursing values of nursing students through factors affecting professional nursing values.

Toxicity prediction of chemicals using OECD test guideline data with graph-based deep learning models (OECD TG데이터를 이용한 그래프 기반 딥러닝 모델 분자 특성 예측)

  • Daehwan Hwang;Changwon Lim
    • The Korean Journal of Applied Statistics
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    • v.37 no.3
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    • pp.355-380
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    • 2024
  • In this paper, we compare the performance of graph-based deep learning models using OECD test guideline (TG) data. OECD TG are a unique tool for assessing the potential effects of chemicals on health and environment. but many guidelines include animal testing. Animal testing is time-consuming and expensive, and has ethical issues, so methods to find or minimize alternatives are being studied. Deep learning is used in various fields using chemicals including toxicity prediciton, and research on graph-based models is particularly active. Our goal is to compare the performance of graph-based deep learning models on OECD TG data to find the best performance model on there. We collected the results of OECD TG from the website eChemportal.org operated by the OECD, and chemicals that were impossible or inappropriate to learn were removed through pre-processing. The toxicity prediction performance of five graph-based models was compared using the collected OECD TG data and MoleculeNet data, a benchmark dataset for predicting chemical properties.

On Tests for Marginal Homogeneity (주변동질성 검정법의 비교분석)

  • 강민희;박태성;이성곤
    • The Korean Journal of Applied Statistics
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    • v.14 no.1
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    • pp.211-221
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    • 2001
  • 본 논문에서는 2$\times$2 분할표의 주변동질성 검정에서 사용될 수 있는 통계량들을 소개하고, 이 통계량들을 비교하였다. 먼저 주변동질성 검정에 민감하게 영향을 주는 모수를 정의한 후에 이 모수들의 효과를 예시하였다. 또한 이 모수들을 이용하여 모의실험을 통해여러 검정법들을 비교해본 결과 McNemar 검정이 다른 검정력보다 더 좋은 성질을 가지고 있음을 보였다.

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Using a Normal Test Variable(NTV) for clinical research (임상 자료 분석을 위한 NORMAL TEST VARIABLE(NTV)의 고찰)

  • 이제영;우정수;최달우
    • The Korean Journal of Applied Statistics
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    • v.11 no.1
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    • pp.129-139
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    • 1998
  • This article examines the use and some difficulties of Normal Test Variables(NTV) plot for clinical research. Monte Carlo Simulation results are presented based on Normal, Bimodal, Uniform, Exponential and skewed-right distributed Beta Distributions. Further, some solutions are presented and illustrated.

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