• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.903-909
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• 1997

The ordinary least squares estimator and the corresponding pivotal statistics have been widely used for the unit test. Recently several test criteria based on maximum likelihood estimators and weighted symmetric estimator have been proposed for testing the unit root hypothesis in the autoregressive processes. Pantula at el. (1994) showed that the weighted symmetric estimator has good power properties. In this article we use an adjusted estimator for mean in the model when we use weighted symmetric estimator. A simulation study shows that for the small samples, this new test criterion has better power properties than the weighted symmetric estimator.

• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.121-135
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• 2015

We consider testing equality of mean functions from two samples of functional data. A novel test based on the adaptive Neyman methodology applied to the Hotelling's T-squared statistic is proposed. Under the enlarged null hypothesis that the distributions of the two populations are the same, randomization methods are proposed to find a null distribution which gives accurate significance levels. An extensive simulation study is presented which shows that the proposed test works very well in comparison with several other methods under a variety of alternatives and is one of the best methods for all alternatives, whereas the other methods all show weak power at some alternatives. An application to a real-world data set demonstrates the applicability of the method.

• Journal of the Korean Statistical Society
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• v.19 no.2
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• pp.128-138
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• 1990

In this paper we study the properties of nonparametric tests for testing the null hypothesis of no changes against one sided and two sideds alternatives in scale parameter at unknown point. We first propose two types of nonparametric tests based on linear rank statistics and rank-like statistics, respectively. For these statistics, we drive the asymptotic distributions under the null and contiguous alternatives. The main theoreticla tools used for derivation are the stochastic process representation of the test staistic and the Brownian bridge approximation. We evaluate the Pitman efficiencies of the test for the contiguous alternatives, and also compute empirical power by Monte Carlo simulation.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.215-230
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• 2016

The powers of some tests for independence hypothesis against positive (negative) quadrant dependence in generalized Farlie-Gumbel-Morgenstern distribution are compared graphically by simulation. Some of these tests are usual linear rank tests of independence. Two other possible rank tests of independence are locally most powerful rank test and a powerful nonparametric test based on the $Cram{\acute{e}}r-von$ Mises statistic. We also evaluate the empirical power of the class of distribution-free tests proposed by Kochar and Gupta (1987) based on the asymptotic distribution of a U-statistic and the test statistic proposed by $G{\ddot{u}}ven$ and Kotz (2008) in generalized Farlie-Gumbel-Morgenstern distribution. Tests of independence are also compared for sample sizes n = 20, 30, 50, empirically. Finally, we apply two examples to illustrate the results.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1115-1124
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• 2010

Normal approximation methods under the null hypothesis of no difference are frequently used to test the two independent proportions in non-inferiority trials. However, these tests are not appropriate under the null hypothesis of non-zero difference. We review the likelihood score methods proposed by Miettinen and Nurminen, Farrington and Manning, and Gart and Nam and compare the performance of these tests. The simulation study shows that the likelihood score tests under the null hypothesis of non-zero difference have better performance at a Type I error and power than usual normal approximation methods.

• Journal of Korean Clinical Nursing Research
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• v.14 no.1
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• pp.33-44
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• 2008

Purpose: This study was performed to determine the effects of foot reflexology on pain and quality of sleep in patients with terminal cancer. Method: Quai-experimental research design was used. The subjects of this study were consisted of 19 for experimental group and 18 for control group. Visualue Scale(VAS) was used as the measurement tool of pain in this study, Verra & Snyder-Halpern Sleep Scale(VSH) and Visual Analogue Scale(VAS) were used as the measurement tool of perceived quality of sleep. Data were analyzed using statistical methods such as frequency, percent, $x^2$-test, t-test using SPSS WIN 12.0 program. Results: The hypothesis 1 that the experimental group with reflexology has less degree of pain than the control group without reflexology was supported (t=5.41, p<.001). The hypothesis 2 that the experimental group with reflexology has higher degree of VSH Scale than the control group without reflexology was supported(t=2.37, p=.02). The hypothesis 3 that the experimental group with reflexology has the difference among the mean of sleep VAS Scale during the 12 measurement periods was not supported(F=1.63, p=.08), and no significant interactions between group and time. Conclusion: It is considered that reflexology is effective for reducing cancer pain and improving quality of sleep in patients with terminal cancer.

• Journal of Families and Better Life
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• v.1 no.2
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• pp.75-88
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• 1983

This study intends to examine the relations between the demographical and the socioeconomic variables on the post-purchase behavior of durable goods in rural household . Several concrete hypothesis in the above study were set as follows: 1) The evaluation on the post-purchase of rural household might be differently made in accordance with sex, age, resident district, education level, income level, family type and user's own purchasing, etc. 2)There can be differences in the attitude on the post-purchase of rural household in accordance with sex, age, resident district, education level, income level, family type and user's own purchasing, etc. 3) It must be of necessity to habe correlation between the evaluation and the attitude of the post- purchase. To examine these hypothesis, the study used the 27 questionnaires which are composed of 7 subject for general characteristics and 10 subjects respectively for the post-purchase evaluation and attitude of 285 rural households in Chon Nam Province. They were interviewed for 11days from Apr. 1st, 1983 to Apr. 11 the, 1983. Statistical methods such as frequency, percentage, Chi-Square test, arithmetical mean, t-test, F-test and Pearson's correlation coefficients, etc. are used for the data analysis. The summary and the conclusion resulted form such analysis are as follows; First, high significances are shown on the age the resident district the education level and the family type as significant variables affecting on the post-purchase evaluation of the rural house hold. Second, high significances are shown on the education level, the income level, the family type and the users own purchasing, etc. as significant variables affecting on the post-purchase attitude of rural household. Third, correlations between the post-purchase evaluation and the post-purchase attitude are very close. Therefore the hypothesis 1)and 2) of this study were accepted partially and the hypothesis 3) was confirmed wholely.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1559-1565
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• 2007

The many target-detection methods that use forward-looking infrared (FUR) images can deal with large targets measuring $70{\times}40$ pixels, utilizing their shape features. However, detection small targets is difficult because they are more obscure and there are many target-like objects. Therefore, few studies have examined how to detect small targets consisting of fewer than $30{\times}10$ pixels. This paper presents a small target detection method using clutter rejection with stochastic hypothesis testing for FLIR imagery. The proposed algorithm consists of two stages; detection and clutter rejection. In the detection stage, the mean of the input FLIR image is first removed and then the image is segmented using Otsu's method. A closing operation is also applied during the detection stage in order to merge any single targets detected separately. Then, the residual of the clutters is eliminated using statistical hypothesis testing based on the t-test. Several FLIR images are used to prove the performance of the proposed algorithm. The experimental results show that the proposed algorithm accurately detects small targets (Jess than $30{\times}10$ pixels) with a low false alarm rate compared to the center-surround difference method using the receiver operating characteristics (ROC) curve.

• Integrative Medicine Research
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• v.6 no.3
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• pp.254-259
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• 2017

Background: Those classified as Tae-Eum (TE)-type people in Sasang constitutional medicine (SCM) are prone to obesity. Although extensive clinical observations have confirmed this tendency, the underlying physiological mechanisms are unknown. Here, we propose a novel hypothesis using integrative physiology to explain this phenomenon. Methods: Hypoactive lung function in the TE type indicates that respiration is attenuated at the cellular level - specifically, mitochondrial oxygen consumption. Because a functional reduction in cellular energy metabolism is suggestive of intrinsic hypoactivity in the consumption (or production) of metabolic energy, we reasoned that this tendency can readily cause weight gain via an increase in anabolism. Thus, this relationship can be derived from the graph of cellular metabolic power plotted against body weight. We analyzed the clinical data of 548 individuals to test this hypothesis. Results: The statistical analysis revealed that the cellular metabolic rate was lower in TEtype individuals and that their percentage of obesity (body mass index >25) was significantly higher compared to other constitutional groups. Conclusion: Lower cellular metabolic power can be an explanation for the obesity trend in TE type people.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.695-708
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• 2011

Image fusion is the process of combining multiple images of the same scene into a single fused image with application to many fields, such as remote sensing, computer vision, robotics, medical imaging and military affairs. The widely used image fusion rules that use wavelet transform have been based on a simple comparison with the activity measures of local windows such as mean and standard deviation. In this case, information features from the original images are excluded in the fusion image and distorted fusion images are obtained for noisy images. In this paper, we propose the use of a nonparametric squared ranks test on the quality of variance for two samples in order to overcome the influence of the noise and guarantee the homogeneity of the fused image. We evaluate the method both quantitatively and qualitatively for image fusion as well as compare it to some existing fusion methods. Experimental results indicate that the proposed method is effective and provides satisfactory fusion results.