• Journal of Wetlands Research
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• v.20 no.2
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• pp.105-115
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• 2018

The frequency analysis of hydrometeorological data is one of the most important factors in response to natural disaster damage, and design standards for a disaster prevention facilities. In case of frequency analysis of hydrometeorological data, it assumes that observation data have statistical stationarity, and a parametric method considering the parameter of probability distribution is applied. For a parametric method, it is necessary to sufficiently collect reliable data; however, snowfall observations are needed to compensate for insufficient data in Korea, because of reducing the number of days for snowfall observations and mean maximum daily snowfall depth due to climate change. In this study, we conducted the frequency analysis for snowfall using the Bootstrap method and SIR algorithm which are the resampling methods that can overcome the problems of insufficient data. For the 58 meteorological stations distributed evenly in Korea, the probability of snowfall depth was estimated by non-parametric frequency analysis using the maximum daily snowfall depth data. The results of frequency based snowfall depth show that most stations representing the rate of change were found to be consistent in both parametric and non-parametric frequency analysis. According to the results, observed data and Bootstrap method showed a difference of -19.2% to 3.9%, and the Bootstrap method and SIR(Sampling Importance Resampling) algorithm showed a difference of -7.7 to 137.8%. This study shows that the resampling methods can do the frequency analysis of the snowfall depth that has insufficient observed samples, which can be applied to interpretation of other natural disasters such as summer typhoons with seasonal characteristics.

• Journal of Veterinary Clinics
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• v.27 no.1
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• pp.66-70
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• 2010

Reference interval is critical for interpreting laboratory results, monitoring response to therapy and predicting the prognosis of the patients in clinical settings. The aim of the present study was to update established reference intervals for routine hematologic and serum chemistry values for a population of clinically healthy dogs (range, 1-8 years) seen in an animal hospital. Blood was obtained by venipuncture while animals were physically restrained, and samples were analyzed for 9 chemistries on MS9-5H (Melot Schloesing Lab, France) and 6 hematology on Vet Test 8008 (IDEXX, USA). Data from 105 dogs (52 males and 53 females) for hematology and 113 dogs (37 males and 76 females) for chemistry were used to determine reference intervals using the parametric, nonparametric and bootstrap methods. Prior to analysis, all parameters were tested for normal distribution using Anderson-Darling criterion. Of the 9 biochemical analytes, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, creatinine, total protein, and glucose concentrations did not fit normal distribution for both original and transformed data. All but eosinophil count satisfied normal distribution for either original or transformed data. Parametric method can be used for original cholesterol concentrations, RBC, WBC, and neutrophil counts. This technique can also be used for power-transformed values of blood urea nitrogen concentrations and for logarithm of lymphocyte and monocyte counts. Non-parametric or bootstrap method was the preferred choice for the remaining 7 biochemical parameters and eosinophil count as they did not follow normal distributions. All three statistical techniques performed in similar reference intervals. When establishing reference intervals for clinical laboratory data, it is essential to assess the distribution of the original data to increase the accuracy of the interval, and non-parametric or bootstrap methods are of alternative for the data that do not fit normal distribution.

• Structural Engineering and Mechanics
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• v.76 no.5
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• pp.631-641
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• 2020

In the present work, an approach for the multiple time probabilistic characterization of the response of linear structural systems subjected to random non-Gaussian processes is presented. Its fundamental property is working directly on the multiple time probability density functions of the actions and of the response. This avoids of passing through the evaluation of the response statistical moments at multiple time or correlations, reducing the computational effort in a consistent measure. This approach is the extension to the multiple time case of a previously published dynamic Probability Transformation Method (PTM) working on a single evolution of the response statistics. The application to some simple examples has revealed the efficiency of the method, both in terms of computational effort and in terms of accuracy.

• Journal of Korean Society on Water Environment
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• v.20 no.1
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• pp.63-71
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• 2004

The long-tenn trend analyses of water qualities were performed for 49 monitoring stations located in Nakdong River. Water quality parameters used in this study are the monthly data of BOD(Biological Oxygen Demand), TN(Total Nitrogen) and TP(Total Phosphorus) measured from 1990 to 1999. The long-tenn trends were analyzed by Seasonal Mann-Kendall Test and Locally WEighted Scatter plot Smoother(LOWESS). Nakdong river was divided into four subbasins, including upstream watershed, midstream watershed, western downstream watershed and eastern downstream watershed. The results of Seasonal Mann-Kendall Test indicated that there would be no trends of BOD in upstream watershed, western and eastern downstream watershed. Trends of BOD were downward in midstream watershed. For TN and TP, there were upward trends in all of watersheds. But LOWESS curves suggested that BOD, TN and TP concentrations generally increased between 1990 and 1996, then resumed decreasing.

• Korean Journal of Acupuncture
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• v.30 no.1
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• pp.1-8
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• 2013

Objectives : The purpose of the present study was to examine statistical methods used in articles published on the Korean Journal of Acupuncture from 2007 through 2012. Methods : Statistical methods and statistical packages used in original articles applied with descriptive statistics or inferential statistics were organized. Results : Out of a total of 195 original articles, 18 articles used descriptive statistics only and 177 articles used inferential statistics. 142 articles used 12 types of statistical packages. SPSS was used most at 97 times(63.4%). The number of descriptive statistical methods used was a total of 417 and among them 193 were presented as tables(46.3%) and 224 were presented as graphs(53.7%). The number of inferential statistics applied was a total of 256 and analysis of variance was used most at 90 times(35.2%). The number of parametric statistical methods used was a total of 170(75.6%) and that of nonparametric statistical methods used was a total of 55(24.4%). Analysis of variance and two sample t-test were most employed in both clinical and non-clinical research. The number of multiple comparison methods applied was a total of 67 and the number of Scheffe methods among them was most at 26 times(37.7%). Conclusions : In the present study, statistical methods used in the journal over the last six years were examined. The result of this study is considered to be a basic material to be referred to when evaluating the quality of the medical journal.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.567-578
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• 2017

Grouped multivariate data can be tested for differences between two or more groups using multivariate analysis of variance (MANOVA). However, this method cannot be used if several assumptions of MANOVA are violated. In this case, multidimensional scaling (MDS) and analysis of distance (AOD) can be applied to grouped dissimilarities based on the various distances. A permutation test is a non-parametric method that can also be used to test differences between groups. MDS is used to calculate the coordinates of observations from dissimilarities and AOD is useful for finding group structure using the coordinates. In particular, AOD is mathematically associated with MANOVA if using the Euclidean distance when computing dissimilarities. In this paper, we study the between and within group structure by applying MDS and AOD to the grouped dissimilarities. In addition, we propose a new test statistic using the group structure for the permutation test. Finally, we investigate the relationship between AOD and MANOVA from dissimilarities based on the Euclidean distance.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.115-121
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• 2017

This paper is to introduce the main modeling assumptions and data structures associated with right-censored data to describe the successful methodological ideas for analyzing such a field-failure-data when components operating in different environments. The Kaplan - Meier method is the most popular method used for survival analysis. Together with the log-rank test, it may provide us with an opportunity to estimate survival probabilities and to compare survival between groups. An important advantage of the Kaplan - Meier curve is that the method can take into account some types of censored data, particularly right-censoring. The above non-parametric method was used to verify the equality of parts life used in different environments. After that, we performed the life distribution analysis using the parametric method. We simulated data from three distributions: exponential, normal, and Weibull. This allowed us to compare the results of the estimates to the known true values and to quantify the reliability indices. Here we used the Akaike information criterion to find a suitable life time distribution. If the Akaike information criterion is the smallest, the best model of failure data is presented. In this paper, no-nparametrics and parametrics methods are analyzed using R program which is a popular statistical program.

• Structural Engineering and Mechanics
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• v.89 no.1
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• pp.61-75
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• 2024

Strengthening of hollow structural sections using through-bolts is a cost-effective and straightforward approach. It's a versatile method that can be applied during both design and service phases, serving as a non-disruptive and budget-friendly retrofitting solution. Existing research on axially loaded hollow sections T-joints has demonstrated that this technique can amplify the joint strength by 50%, where single bolt could enhance the strength of the joint by 35%. However, there's a gap in understanding their use for K-joints. As the behavior of K-joints is more complex, and they are widely existent in structures, this study aims to bridge that gap by conducting comprehensive parametric study using finite element analysis. Numerical investigation was conducted to evaluate the effect of through bolts on K-joints focusing on using single through bolt to achieve most of the strengthening effect. A full-scale parametric model was developed to investigate the effect of various geometric parameters of the joint. This study concluded the existence of optimal bolt location to achieve the highest strength gain for the joint. Moreover, a rigorous statistical analysis was conducted on the data to propose design equations to predict optimal bolt location and the corresponding strength gain implementing the verified by finite element models.

• Computers and Concrete
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• v.32 no.4
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• pp.425-438
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• 2023

In this article, the performance of steel fiber-reinforced concrete (SFRC) flat slabs was investigated numerically. The influence of flexural steel reinforcement, steel fiber content, concrete compressive strength, and slab thickness were discussed. The numerical model was developed using ATENA-Gid, user-friendly software for non-linear structural analysis for the evaluation and design of reinforced concrete elements. The numerical model was calibrated based on eight experimental tests selected from the literature to validate the actual behavior of steel fiber in the numerical analysis. Then, a parametric study of 144 specimens was generated and discussed the impact of various parameters on the punching shear strength, and statistical analysis was carried out. The results showed that slab thickness, steel fiber content, and concrete compressive strength positively affect the punching shear capacity. The fib Model Code 2010 for specimens without steel fibers and the model of Muttoni and Ruiz for SFRC specimens presented a good agreement with the results of this study.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.489-499
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• 2018

Jeonse is a unique property rental system in Korea in which a tenant pays a part of the price of a leased property as a fixed amount security deposit and gets back the entire deposit when the tenant moves out at the end of the tenancy. Jeonse deposit is very important in the Korean real estate market since it is directly related to the residential property sales price and it is a key indicator to predict future real estate market trend. Jeonse deposit data shows a skewed and heteroscedastic distribution and the commonly used mean regression model may be inappropriate for the analysis of Jeonse deposit data. In this paper, we apply a Bayesian quantile regression model to analyze Jeonse deposit data, which is non-parametric and does not require any distributional assumptions. Analysis results show that the quantile regression coefficients of most explanatory variables change dramatically for different quantiles. The regression coefficients of some variables have different signs for different quantiles, implying that even the same variable may affect the Jeonse deposit in the opposite direction depending on the amount of deposit.