• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.39-52
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• 2007

Crossover trials of new drugs in the treatment of angina pectoris, which frequently use treadmill exercise test for the assessment of its efficacy, produce censored survival times. In this paper we consider analysis approaches for censored survival times from crossover trials. Previously, a stratified Cox model for paired observation and nonparametric methods have been presented as possible analysis methods. On the other hand, the differences of two survival times would produce interval-censored survival times and we propose a Cox model for interval-censored data as n alternative analysis method. Example data is analyzed in order to compare these different methods.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.1065-1075
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• 2008

For the model validation of credit rating models, Kolmogorov-Smirnov(K-S) statistic has been widely used as a testing method of discriminatory power from the probabilities of default for default and non-default. For the credit rating works, K-S statistics are to test two identical distribution functions which are partitioned from a distribution. In this paper under the assumption that the distribution is known, modified K-S statistic which is formulated by using known distributions is proposed and compared K-S statistic.

• Journal of Oriental Neuropsychiatry
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• v.19 no.2
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• pp.123-132
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• 2008

Objective: This clinical research is conducted to find out coping strategies and anxiety of patients with chronic pain, and the correlation between pain coping strategy and anxiety. Method: 50 subjects who came to the local oriental clinic answered the questionnaires about VPMI(Vanderbilt Pain Management Inventory) and SAS(The Self-rating Anxiety Scale). Then we researched the characteristics of pain coping strategies and the correlation. Results: 1. The mean scores of passive coping, active coping, and SAS are 29.62, 17.90, and 38.32 respectively. 2. In the analysis of nonparametric test, the female subjects tend to take more passive coping than the male. The older subjects tend to take less active coping than the younger. Subjects who reported more intense pain tend to take more passive coping. 3. There is significant difference between passive coping and anxiety. Conclusion: Pain coping strategies are related with age, sex, intensity of pain, and anxiety. The therapeutic intervention of decreasing passive coping and increasing active coping may be useful to manage the chronic pain. Further study is needed to find out more adequate inquiries of active coping.

• Journal of the Korean Society for Library and Information Science
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• v.41 no.2
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• pp.237-256
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• 2007

This study examined DEA(Data Envelopment Analysis) and how it measures the efficiency of library units. DEA is a useful nonparametric method to evaluate the relative efficiency of a set of decision making units(DMUs) with multiple inputs and outputs. This study evaluated 102 different public libraries utilizing 4 inputs and 4 outputs focussing on the year 2005. For inefficient libraries, the study analysed the potential improvement and the source of inefficiency comparing the peer groups. The result of this study shows that efficiency of public libraries varies in different localities and forms of operation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.306-311
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• 2008

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise. It can also serve as a sound methodology that can be applied to a variety of management and engineering problems where variables are interacting in an uncertain, qualitative, and fuzzy way. A close examination of the fuzzy regression algorithm reveals that the resulting possibility distribution of fuzzy parameters, which makes this technique attractive in a fuzzy environment, is dependent upon an h parameter value. The h value, which is between 0 and 1, is referred to as the degree of fit of the estimated fuzzy linear model to the given data, and is subjectively selected by a decision maker (DM) as an input to the model. The selection of a proper value of h is important in fuzzy regression, because it determines the range of the posibility ditributions of the fuzzy parameters. In this paper, we discuss the interdependent relationship among the h value, membership function shape, and the spreads of fuzzy parameters in fuzzy linear regression with fuzzy input-output using shape-preserving operations.

• Journal of Communications and Networks
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• v.6 no.1
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• pp.68-77
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• 2004

In the near future packet networks should support applications which can not predict their traffic requirements in advance, but still have tight quality of service requirements, e.g., guaranteed bandwidth, jitter, and packet loss. These dynamic characteristics mean that the sources can be made to modify their data transfer rates according to network conditions. Depending on the customer&; needs, network operator can differentiate incoming connections and handle those in the buffers and the interfaces in different ways. In this paper, dynamic QoS-aware scheduling algorithm is presented and investigated in the single node case. The purpose of the algorithm is in addition to fair resource sharing to different types of traffic classes with different priorities ?to maximize revenue of the service provider. It is derived from the linear type of revenue target function, and closed form globally optimal formula is presented. The method is computationally inexpensive, while still producing maximal revenue. Due to the simplicity of the algorithm, it can operate in the highly nonstationary environments. In addition, it is nonparametric and deterministic in the sense that it uses only the information about the number of users and their traffic classes, not about call density functions or duration distributions. Also, Call Admission Control (CAC) mechanism is used by hypothesis testing.

• Structural Monitoring and Maintenance
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• v.6 no.1
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• pp.33-46
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• 2019

In present study, Operational Modal Analysis (OMA) was employed to carry out the dynamic and vibration analysis of the threshing unit of the combine harvester thresher as a mechanical component. The main study is to find the causes of vibration and to decrease it to enhance the lifetime and efficiency of the threshing unit. By utilizing OMA, structural modal parameters such as mode shapes, natural frequencies, and damping ratio was calculated. The combine harvester was excited by engine to vibrate different parts and accelerometer sensor collected acceleration signals at different speeds, and OMA was utilized by nonparametric and frequency analysis methods to obtain modal parameters while vibrating in real working conditions. Afterwards, finite element model was designed from the thresher and updated using the data obtained from the modal analysis. Using the conducted analyses, it was specified that proximity of the thresher pass frequency to one of the natural frequencies (16.64 Hz) was the most important effect of vibration in the thresher. Modification process of the structure was carried out by increasing mass required for changing the natural frequency location of the first mode to 12.4 Hz in order to reduce resonance and vibration of the thresher.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.48.4-49
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• 2020

We reconstruct the expansion history of the universe using type Ia supernovae (SN Ia) in a manner independent of any cosmological model assumptions. To do so, we implement a nonparametric iterative smoothing method on the Joint Light-curve Analysis (JLA) data while exploring the SN Ia light-curve hyperparameter space by Markov Chain Monte Carlo (MCMC) sampling. We test to see how the posteriors of these hyperparameters depend on cosmology, whether using different dark energy models or reconstructions shift these posteriors. Our constraints on the SN Ia light-curve hyperparameters from our model-independent analysis are very consistent with the constraints from using different parameterizations of the equation of state of dark energy, namely the flat ΛCDM cosmology, the Chevallier-Polarski-Linder model, and the Phenomenologically Emergent Dark Energy (PEDE) model. This implies that the distance moduli constructed from the JLA data are mostly independent of the cosmological models. We also studied that the possibility the light-curve parameters evolve with redshift and our results show consistency with no evolution. The reconstructed expansion history of the universe and dark energy properties also seem to be in good agreement with the expectations of the standard ΛCDM model. However, our results also indicate that the data still allow for considerable flexibility in the expansion history of the universe. This work is published in ApJ.

• Korea Trade Review
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• v.47 no.3
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• pp.17-35
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• 2022

The Pandemic crisis caused by COVID-19 has raised awareness of the importance of supply chain risk management, such as the control of movement between countries and the simultaneous manufacturing paralysis in the world. Effective risk management within the supply chain of the company is a core competency in the global environment. Therefore, this study quantitatively analyzed the perspective of domestic large corporations and small and medium enterprises (SMEs) by using the hierarchical analysis method (AHP) to identify the factors that should be considered as the priority when establishing supply chain risk management plans for large and small business employees. In order to conduct the study, a survey was conducted on large corporations and small and medium enterprises in Gyeongnam and Busan, and AHP analysis was conducted using Microsoft 365 excel program. In addition, Mann-Whitney U test (independent sample-nonparametric test) was conducted using SPSS/18 version of statistical package program for comparative analysis between groups. As a result, the priority was highly evaluated in the order of financial ability, competitiveness, disaster in the overall priority evaluation. There were statistically significant differences in internal risk and strategic decision making of supply chain between groups. This suggests that fandemics such as COVID-19 can not be predicted, but strategic responses are needed to utilize opportunities expressed in the crisis through supply chain risk management and to increase the competitive advantage of domestic companies even in the crisis.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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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.