• Journal of the Korean Mathematical Society
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• v.47 no.2
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• pp.385-407
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• 2010

To study the relationship between the levels of chemical pollutants and the number of daily total hospital admissions for respiratory diseases and to find the effect of temperature/relative humidity on the admission number, Wong et al. [17] introduced the varying-coefficient single-index model (VCSIM). As pointed out, it is a popular multivariate nonparametric fitting technique. However, the tests of the model have not been very well developed. In this paper, based on the estimators obtained by the local linear technique, the average method and the one-step back-fitting technique in the VCSIM, the generalized likelihood ratio (GLR) tests for varying-coefficient parts on the VCSIM are established. Under the null hypotheses the new proposed GLR tests follow the $\chi^2$-distribution asymptotically with scale constant and degree of freedom independent of the nuisance parameters, known as Wilks phenomenon. Simulations are conducted to evaluate the test procedure empirically. A real example is used to illustrate the performance of the testing approach.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.5
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• pp.145-152
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• 2001

농촌유역하천에서 수집된 수질측정자료를 이용하여 주요 오염원을 규명하였다. 분석에 이용된 수질항목은 BOD, COD. EC, pH. TN, TP,$NO_3-N,PO_4-P$ 등으로서 하천 본류내 구간별로 쌍대비교를 통해서 항목별 차이에 대한 유의성 검정을 하였다. 유의성 검정에 이용된 방법은 쌍대비교를 위한 비모수검정법인 Wilcoxon 순위검정법을 이용하였다. 검정결과, 유기성 오염물질의 지표로 이용되는 BOD와 COD가 상승하는 구간은 주로 생활하수가 유입되는 구간으로 나타났다. 인구밀도가 매우 높으나 생활하수가 처리장으로 배제되는 지역의 하천구간에서는 이들 농도변화는 없었다. 유역 내 축산농가가 밀집되어 있는 지역의 하천구간에서도 농도의 변화 또한 존재하지 않았다. 본 연구에서 조사된 유역에서와 같이 축산분뇨를 퇴비화 및 농지환원하는 경우에는 하천수질에 거의 영향을 미치지 않는다는 것을 알 수 있었다. 따라서 농촌지역의 하천 수질을 개선하기 위해서는 생활하수에 대한 처리가 선행되어야 한다.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.215-218
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• 2002

The edges of an image hold much of the information in that image. The edges tell where objects are, their shape and size, and something about their texture. An edge is where the intensity of an image moves from a low value to a high value. We introduce the edge detection using the differential operator with Sobel operator and describe a nonparametric Wilcoxon test based on statistical hypothesis testing for the detection of edges. This paper proposes an efficient edge detection using Van der Waerden's statistic in original and noisy images. We use the threshold determined by specifying significance level a and an edge-height parameter. Comparison with our statistical test and Sobel operator shows that Van der Waerden method perform more effectively in both noisy and noise-free images.

• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.571-584
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• 2024

To identify differentially expressed genes (DEGs), researchers use a testing method for each gene. However, microarray data are often characterized by large dimensionality and a small sample size, which lead to problems such as reduced analytical power and increased number of tests. Therefore, we propose a clustering method. In this method, genes with similar expression patterns are clustered, and tests are conducted for each cluster. This method increased the sample size for each test and reduced the number of tests. In this case, we used a nonparametric permutation test in the proposed method because independence between samples cannot be assumed if there is a relationship between genes. We compared the accuracy of the proposed method with that of conventional methods. In the simulations, each method was applied to the data generated under a positive correlation between genes, and the area under the curve, power, and type-one error were calculated. The results show that the proposed method outperforms the conventional method in all cases under the simulated conditions. We also found that when independence between samples cannot be assumed, the non-parametric permutation test controls the type-one error better than the t-test.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.237-248
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• 2009

The probability of default on the credit evaluation study is represented as a linear combination of two distributions of default and non-default, and the distribution of the probability of default are generally known in most cases. Except the well-known Kolmogorov-Smirnov statistic for testing the identity of two distribution, Kuiper, Cramer-Von Mises, Anderson-Darling, and Watson test statistics are introduced in this work. Under the assumption that the population distribution is known, modified Cramer-Von Mises, Anderson-Darling, and Watson statistics are proposed. Based on score data generated from various probability density functions of the probability of default, the modified test statistics are discussed and compared.

• Journal of Korean Physical Therapy Science
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• v.13 no.1
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• pp.39-52
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• 2006

The purpose of this study was to investigate the effects of lumbar stabilization exercise therapy on low back pain patients' lumbar spinal function. Identify the effect of stabilization exercise therapy, this study attempted to determine lumbar spinal functions, using spinoscopy, for 20 patients with low back pain This study applied lumbar stabilization exercise to 20 low back pain patients without a control group for 8 weeks and 4 times a week, and examined their spinal functions before and after the application. Data collected from the test were analyzed using Wilcoxon signed ranked test, a nonparametric test. Absolute index, functionality and performance increased significantly compared to them before treatment. FE loads and velocity control while conducting exercise tasks increased significantly compared to them before treatment. Test item ROL and ROM, which indicate the change of angle, both showed significant differences. Of stiff spine, stiff pelvic score and sprain score, which indicate the effects of the conduct of exercise tasks on the movement of the spine, stiff spine score and sprain score showed significant differences. According to the results as presented above, lumbar stabilization exercise may be greatly helpful in improving low back pain patients' lumbar spinal functions.

• Journal of Korean Academy of Rural Health Nursing
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• v.11 no.2
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• pp.17-28
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• 2016

Purpose: This study aimed to determine the effects of a 'Customized Integrated Health Care Program' for male living alone in a single region and assist health promotion of the participants. Methods: This study was one-group pretest-posttest design. Eleven participants in the 'Happy Cooking Class for Male Living Alone' who made 100% of attendance from February 18 to September 8, 2016 were analyzed. Nonparametric paired T-test was performed to determine the differences in Blood pressure(BP), Blood sugar(BS), Cholesterol, Hemoglobin(Hb), Dementia screening test, Depression screening test of the participants in the Customized Integrated Health Care Program. Results: After applying the 'Customized Integrated Health Care Program', Hb level(z=-2.724, p=.006) and Dementia screening test(z=-1.974, p=.048) increased statistically significantly. Conclusion: As the elderly living alone increase in number, it seems that social support networks and health care programs contribute to health promotion of the participants and positively affect the rest of their life.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.769-777
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• 1998

In this study, various time series are analyzed to check nonlinearities of the data. The nonlinearity of a system can be investigated by testing the randomness of the time series data. To test the randomness, four nonparametric test statistics and a new test statistic, called the BDS statistic are used and the results and the results are compared. The Brock, Dechert, and Scheinkman (BDS) statistic is originated from the statistical properties of the correlation integral which is used for searching for chaos and has been shown very effective in distinguishing nonlinear structures in dynamic systems from random structures. As a result of application to linear and nonlinear models which are well known, the BDS statistic is found to be more effective than nonparametric test statistics in identifying nonlinear structure in the time series. Hydrologic time series data are fitted to ARMA type models and the statistics are applied to the residuals. The results show that the BDS statistic can distinguish chaotic nonlinearity from randomness and that the BDS statistic can also be used for verifying the validity of the fitted model.

• Journal of Korea Water Resources Association
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• v.39 no.12 s.173
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• pp.997-1012
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• 2006

We have presented a nonparametric stochastic approach for the SOI(Southern Oscillation Index) series that used nonlinear methodology called Nonlinear AutoRegressive(NAR) based on conditional kernel density function and CAFPE(Corrected Asymptotic Final Prediction Error) lag selection. The fitted linear AR model represents heteroscedasticity, and besides, a BDS(Brock - Dechert - Sheinkman) statistics is rejected. Hence, we applied NAR model to the SOI series. We can identify the lags 1, 2 and 4 are appropriate one, and estimated conditional mean function. There is no autocorrelation of residuals in the Portmanteau Test. However, the null hypothesis of normality and no heteroscedasticity is rejected in the Jarque-Bera Test and ARCH-LM Test, respectively. Moreover, the lag selection for conditional standard deviation function with CAFPE provides lags 3, 8 and 9. As the results of conditional standard deviation analysis, all I.I.D assumptions of the residuals are accepted. Particularly, the BDS statistics is accepted at the 95% and 99% significance level. Finally, we split the SOI set into a sample for estimating themodel and a sample for out-of-sample prediction, that is, we conduct the one-step ahead forecasts for the last 97 values (15%). The NAR model shows a MSEP of 0.5464 that is 7% lower than those of the linear model. Hence, the relevance of the NAR model may be proved in these results, and the nonparametric NAR model is encouraging rather than a linear one to reflect the nonlinearity of SOI series.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.44 no.1
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• pp.25-28
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• 2018

Objectives: This study aimed to describe recent patterns in the types of statistical test used in original articles that were published in Journal of the Korean Association of Oral and Maxillofacial Surgeons. Materials and Methods: Thirty-six original articles published in the Journal in 2015 and 2016 were ascertained. The type of statistical test was identified by one researcher. Descriptive statistics, such as frequency, rank, and proportion, were calculated. Graphical statistics, such as a histogram, were constructed to reveal the overall utilization pattern of statistical test types. Results: Twenty-two types of statistical test were used. Statistical test type was not reported in four original articles and classified as unclear in 5%. The four most frequently used statistical tests constituted 47% of the total tests and these were the chi-square test, Student's t-test, Fisher's exact test, and Mann-Whitney test in descending order. Regression models, such as the Cox proportional hazard model and multiple logistic regression to adjust for potential confounding variables, were used in only 6% of the studies. Normality tests, including the Kolmogorov-Smirnov test, Levene test, Shapiro-Wilk test, and $Scheff{\acute{e}}^{\prime}s$ test, were used diversely but in only 10% of the studies. Conclusion: A total of 22 statistical tests were identified, with four tests occupying almost half of the results. Adoption of a nonparametric test is recommended when the status of normality is vague. Adjustment for confounding variables should be pursued using a multiple regression model when the number of potential confounding variables is numerous.