• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2A
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• pp.196-201
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• 2010

Measurement of Quality of Service (QoS) parameters and its statistical analysis becomes a key issue for Mobile WiMAX service providers to manage the converged network efficiently and to support end-to-end QoS. In this paper, we investigate the population distribution of end-to-end one-way delay which is the most important QoS parameter in Mobile WiMAX networks. The samples are analyzed with Chi-Square Goodness-of-Fit test, Kolmogorov-Smirnov (K-S), and Anderson-Darling (A-D) test to verify the distribution of parent population. The relation with confidence level and the minimum number of sample size is also performed for logistic distribution. The statistical analysis is a promising approach for measuring the performance Mobile WiMAX networks.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.513-528
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• 2017

Statistics are often used to test two samples if they have been drawn from the same underlying distribution. In this paper, we introduce several well-known distribution-free tests to compare distributions and conduct an extensive Monte-Carlo simulation to specify their behaviors. We consider various circumstances of when two distributions vary in (1) location, (2) scale, (3) symmetry, (4) kurtosis, (5) tail weight. A practical guideline for two-sample goodness-of-fit test is presented based on the simulation result.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.4
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• pp.395-400
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• 2009

As the variables affecting the fatigue behavior have uncertainty, the fatigue crack propagation is stochastic in nature. Therefore, the fatigue life prediction is critical for the design and the maintenance of many structural components. In this study, fatigue experiments are conducted on the specimens of magnesium alloy under the different thicknesses of specimen. The effects of specimen thickness on the probability distribution of the fatigue crack propagation life and the crack size are estimated experimentally. The probability distribution of the crack size and the fatigue life for different specimen thicknesses are investigated by Anderson-Darling test and the best fit for those probability distributions are also presented.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.5
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• pp.536-543
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• 2009

In this paper the mean stress effects on the probability distribution of the random grown crack size at a specified loading cycle are studied through the fatigue crack propagation tests, which are conducted on the specimens of magnesium alloy under four different stress ratios. Through 80 replicates the probability distributions of the grown crack size are obtained. The goodness-of-fit for probability distributions of the random grown crack size are investigated by Anderson-Darling test and the best fit for those probability distributions is found to be a 3-parameter Weibull distribution. The effects of the mean stress on the probability distribution of the random grown crack size are also estimated.

• Fire Science and Engineering
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• v.30 no.4
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• pp.121-127
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• 2016

This study analyzed the structural and electrical characteristics of an iron fittings type Corrugated Stainless Steel Tubing (CSST) damaged by the Primary Current Injection Test System (PCITS). CSST consists of cladding, tube, nuts, clamp ring, flare cap, socket, and ball valve. For an evaluation of the dielectric withstand voltage, the area between the live part and non-live part of the CCST shall withstand a voltage of 220 V AC for one minute. For an evaluation of the insulation performance by 500 V DC, it is required that the insulation exceed more than $1M{\Omega}$ before the temperature rise test, $0.3M{\Omega}$ after the test. Although the average resistance of the product was $11.5m{\Omega}$, that of the product damaged at a current of 130 A by the PCITS was $11.50m{\Omega}$. Furthermore, parts of the cladding were melted and black smoke appeared when a current of 130 A applied for 10 s. After 60 s, most parts were heated and turned red. At 120 s, the parts that turned red had widened. Although it did not form a normal distribution because the P value was 0.019 with a confidential interval of 95%, it revealed outstanding characteristics with an AD (Anderson-Darling) value of 0.896 and a standard deviation of 0.5573.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.33-39
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• 2020

In order to cope with traffic accidents efficiently, the maximum number of traffic accidents, deaths and serious injuries that can occur during the day should be presented quantitatively. In order to examine the characteristics of traffic accidents in different regions, it was divided into the Seoul metropolitan area, Chungcheong area, Gyeongbuk area, Honam area, and Gyeongnam area and was suitable for the generalized extreme value distribution (GEV). The parameters of the GEV distribution were estimated by the L-moments, and the Anderson-Darling test and the Cramer-von Mises test confirmed the suitability of the distribution. According to the analysis, the maximum number of traffic accidents that can occur once every 50 years is 401 in the Seoul metropolitan area, 168 in the South Gyeongsang region, 455 in the North Gyeongsang region, 136 in the Chungcheong region and 205 in the South Jeolla region. Compared to the Seoul metropolitan area, which has a large population and car registration, the number of traffic accidents is relatively high due to the large area, mountainous areas, and logistics movement caused by the industrial complex.

• Journal of Environmental Health Sciences
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• v.48 no.5
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• pp.266-271
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• 2022

Background: The selection of distributions of input parameters is an important component in probabilistic exposure assessment. Goodness-of-fit (GOF) methods are used to determine the distribution of exposure factors. However, there are no clear guidelines for choosing an appropriate GOF method. Objectives: The outcomes of probabilistic consumer exposure assessment were compared by using five different GOF methods for the selection of input distributions: chi-squared test, Kolmogorov-Smirnov test (K-S), Anderson-Darling test (A-D), Akaike information criterion (AIC) and Bayesian information criterion (BIC). Methods: Individual exposures were estimated based on product usage factor combinations from 10,000 respondents. The distribution of individual exposure was considered as the true value of population exposures. Results: Among the five GOF methods, probabilistic exposure distributions using the A-D and K-S methods were similar to individual exposure estimations. Comparing the 95th percentiles of the probabilistic distributions and the individual estimations for 10 CPs, there were 0.73 to 1.92 times differences for the A-D method, and 0.73 to 1.60 times differences (excluding tire-shine spray) for the K-S method. Conclusions: There were significant differences in exposure assessment results among the selection of the GOF methods. Therefore, the GOF methods for probabilistic consumer exposure assessment should be carefully selected.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1054-1061
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• 2015

Navigation accuracy, integrity, and safety of commercial Unmanned Aerial Vehicle (UAV) is becoming crucial as utilization of UAV in commercial applications is expected to increase. Recently, the concept of Local-Area Differential GNSS (LADGNSS) which can provide navigation accuracy and integrity of UAV was proposed. LADGNSS can provide differential corrections and separation distances for precise and safe operation of the UAV. In order to derive separation distances between UAVs, modeling of Flight Technical Error (FTE) is required. In most cases, FTE for civil aircraft has been assumed to be zero-mean normal distribution. However, this assumption can cause overconservatism especially for UAV, because UAV may use control and navigation equipments in wider performance range and follow more diverse path than standard airway for civil aircraft. In this research, flight experiments were carried out to understand the characteristics of FTE distribution. Also, this paper proposes to use Johnson distribution which can better describe heavy-tailed and skewed FTE data. Futhermore, Kolmogorov-Smirnov and Anderson-Darling tests were conducted to evaluate the goodness of fit of Johnson model.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.797-810
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• 2017

The Korean peninsula is exposed to typhoons every year. Typhoons cause huge socioeconomic damage because tropical cyclones tend to occur with strong winds and heavy precipitation. In order to understand the complex dependence structure between strong winds and heavy precipitation, the copula links a set of univariate distributions to a multivariate distribution and has been actively studied in the field of hydrology. In this study, we carried out analysis using data of wind speed and precipitation collected from the weather stations in Busan and Jeju. Log-Normal, Gamma, and Weibull distributions were considered to explain marginal distributions of the copula. Kolmogorov-Smirnov, Cramer-von-Mises, and Anderson-Darling test statistics were employed for testing the goodness-of-fit of marginal distribution. Observed pseudo data were calculated through inverse transformation method for establishing the copula. Elliptical, archimedean, and extreme copula were considered to explain the dependence structure between strong winds and heavy precipitation. In selecting the best copula, we employed the Cramer-von-Mises test and cross-validation. In Busan, precipitation according to average wind speed followed t copula and precipitation just as maximum wind speed adopted Clayton copula. In Jeju, precipitation according to maximum wind speed complied Normal copula and average wind speed as stated in precipitation followed Frank copula and maximum wind speed according to precipitation observed Husler-Reiss copula.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.519-531
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• 2017

We consider goodness-of-fit test statistics for Weibull distributions when data are randomly censored and the parameters are unknown. Koziol and Green (Biometrika, 63, 465-474, 1976) proposed the $Cram\acute{e}r$-von Mises statistic's randomly censored version for a simple hypothesis based on the Kaplan-Meier product limit of the distribution function. We apply their idea to the other statistics based on the empirical distribution function such as the Kolmogorov-Smirnov and Liao and Shimokawa (Journal of Statistical Computation and Simulation, 64, 23-48, 1999) statistics. The latter is a hybrid of the Kolmogorov-Smirnov, $Cram\acute{e}r$-von Mises, and Anderson-Darling statistics. These statistics as well as the Koziol-Green statistic are considered as test statistics for randomly censored Weibull distributions with estimated parameters. The null distributions depend on the estimation method since the test statistics are not distribution free when the parameters are estimated. Maximum likelihood estimation and the graphical plotting method with the least squares are considered for parameter estimation. A simulation study enables the Liao-Shimokawa statistic to show a relatively high power in many alternatives; however, the null distribution heavily depends on the parameter estimation. Meanwhile, the Koziol-Green statistic provides moderate power and the null distribution does not significantly change upon the parameter estimation.