• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.857-866
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• 2009

In this study, basic data is consisted annual maximum rainfall at 56 stations that has the rainfall records more than 30years in Korea. The 14 probability distributions which has been widely used in hydrologic frequency analysis are applied to the basic data. The method of moments, method of maximum likelihood and probability weighted moments method are used to estimate the parameters. And 4-tests (chi-square test, Kolmogorov-Smirnov test, Cramer von Mises test, probability plot correlation coefficient (PPCC) test) are used to determine the goodness of fit of probability distributions. This study emphasizes the necessity for considering the variability of the estimate of T-year event in hydrologic frequency analysis and proposes a framework for evaluating probability distribution models. The variability (or estimation error) of T-year event is used as a criterion for model evaluation as well as three goodness of fit criteria (SLSC, MLL, and AIC) in the framework. The Jackknife method plays a important role in estimating the variability. For the annual maxima of rainfall at 56 stations, the Gumble distribution is regarded as the best one among probability distribution models with two or three parameters.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.193-225
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• 2006

The purpose of this paper is to analyze contagion in Asian foreign exchange markets using Extreme Value Theory and Copula. Our application deals with asymptotic dependence of daily exchange rate return for a sample of eight countries over period 1997.1.1-2005.4.13. The empirical results are summarized as follows. Firstly, Gumbel Copula is a good model to our data according to the value of AIC. Secondly, the extremal dependence between East Asian crisis countries became lower in the post crisis period than the crisis period. Thirdly, It seemed that high extremal dependence exists between East Asian countries with Singapore. Fourthly, the tail dependence between Indonesia, Malaysia, Thailand, Philippine became higher in the crisis period than the total period and post crisis period. Fifthly, the fact that the extremal dependence between Korea and Indonesia, Malaysia, Thailand, Philippine did not increase during the Asian Financial Crisis showed that the contagion effect was not the reason of the Korea's Fiancial Crisis. Sixthly, the extremal dependence between Asian exchange markets was not very high while comparing with the European exchange markets.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.163-168
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• 2015

In order to perform estimations with high reliability, it is necessary to deal with the tail part of the cumulative distribution function (CDF) in greater detail compared to an overall CDF. The use of a generalized Pareto distribution (GPD) to model the tail part of a CDF is receiving more research attention with the goal of performing estimations with high reliability. Current studies on GPDs focus on ways to determine the appropriate number of sample points and their parameters. However, even if a proper estimation is made, it can be inaccurate as a result of an incorrect threshold value. Therefore, in this paper, a GPD based on the Akaike information criterion (AIC) is proposed to improve the accuracy of the tail model. The proposed method determines an accurate threshold value using the AIC with the overall samples before estimating the GPD over the threshold. To validate the accuracy of the method, its reliability is compared with that obtained using a general GPD model with an empirical CDF.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.56-67
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• 2015

In this study, a source locating technique applicable to transversely isotropic media was developed. Wave velocity anisotropy was considered based on the partition approximation method, which simply enabled AE source locating. Sets of P wave arrival time were decided by the two-step AIC algorithm and they were later used to locate the AE sources when having the least error compared with the partitioned elements. In order to validate the technique, pencil lead break test on artificial transversely isotropic mortar specimen was carried out. Defining the absolute error as the distance between the pencil lead break point and the located point, 1.60 mm ~ 14.46 mm of range and 8.57 mm of average were estimated therefore it was regarded as thought to be 'acceptable' considering the size of the specimen and the AE sensors. Comparing each absolute error under different threshold levels, results showed small discrepancies therefore this technique was hardly affected by background noise. Absolute error could be decomposed into each coordinate axis error and through it, effect of AE sensor position could be understood so if optimum sensor position was able to be decided, one could get more precise outcome.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.113-117
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• 2016

Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (${\beta}$=0.13, p-value<0.001), for colorectal cancer was in the 75th percentile (${\beta}$=0.048, p-value<0.001), for prostate cancer the 95th percentile (${\beta}$=0.55, p-value<0.001), for lung cancer was in 95th percentile (${\beta}$=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (${\beta}$=0.011, p-value<0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(${\beta}$=0.003, p-value<0.001), for esophageal cancer the 95th (${\beta}$=0.04, p-value=0.4) and for skin cancer also the 95th (${\beta}$=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made.

• Journal of Animal Science and Technology
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• v.51 no.2
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• pp.129-134
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• 2009

The aim of this study was to estimate genetic parameters and annual trends on the racing performance of Thoroughbred horses by a statistical analysis of the resulting records. We used the racing results of 245,979 observations for 13,458 horses recorded in 19 years of race held at Seoul and Busan racing tracks, provided by Korea Racing Authority. After a careful adjustment of some variables such as racing times, jockey and trainer numbers and the average prize a horse won, we selected significant factors that explain the result of racing records of a horse by stepwise AIC and BIC methods. The estimated heritability and repeatability were 0.322 and 0.332, respectively. The average of annual phenotypic and genetic improvement was -0.166 seconds and -0.161 seconds, respectively. Based on the statistical approach, we established reasonable animal model of well-set variables, which is important in the study on estimating performance of racing horses.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.5
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• pp.322-330
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• 2020

Modeling for outliers in time series was carried out using the MSL and extreme high, low tide levels (EHL, HLL) data set in the Busan and Mokpo stations. The time-series model is seasonal ARIMA model including the components of the AO (additive outliers) and LS (level shift). The optimal model was selected based on the AIC value and the model parameters were estimated using the 'tso' function (in 'tsoutliers' package of R). The main results by the model application, i.e.. outliers and level shift detections, are as follows. (1) The two AO are detected in the Busan monthly EHL data and the AO magnitudes were estimated to 65.5 cm (by typhoon MAEMI) and 29.5 cm (by typhoon SANBA), respectively. (2) The one level shift in 1983 is detected in Mokpo monthly MSL data, and the LS magnitude was estimated to 21.2 cm by the Youngsan River tidal estuary barrier construction. On the other hand, the RMS errors are computed about 1.95 cm (MSL), 5.11 cm (EHL), and 6.50 cm (ELL) in Busan station, and about 2.10 cm (MSL), 11.80 cm (EHL), and 9.14 cm (ELL) in Mokpo station, respectively.

• Journal of Animal Science and Technology
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• v.52 no.3
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• pp.187-190
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• 2010

The objective of this study was to estimate genetic parameters for total number of born (TNB), number of born alive (NBA) and teat numbers (TN) of Landrace and Yorkshire breeds in Korean swine population using multiple trait animal model procedures. Total numbers of 4,653 records for teat numbers and 8,907 records for TNB and NBA collected from 2004 to 2008 on imported breeding pigs and their litter size records were used in this study. To find the appropriate model for estimation of genetic parameters (heritabilities and genetic correlations), five statistical models (two models for reproductive traits, two models for teat numbers, one model for combining these traits) considering only direct additive genetic effects, including maternal effects were used and Akaike information criteria (AIC) of each two models for reproductive traits and teat trait were compared. The means and standard deviations of TNB, NBA, and TN were $11.52{\pm}3.34$, $10.55{\pm}2.96$ and $14.30{\pm}0.83$, respectively. Estimated heritabilities for TNB and NBA traits using the model which considered only additive genetic effect were low (0.06 and 0.05, respectively). However, estimated heritabilities considering maternal genetic effects were a little bit higher than that of the model considering only additive genetic effect (0.09 for TNB and NBA, respectively). Estimated heritability for TN using the model which considered only additive genetic effect was 0.40. However, estimated heritability of direct genetic effects from a model considering maternal genetic effect was high (0.60). All results of AIC statistics, the models considering maternal effect was more appropriate than the models considering only additive genetic effect. Genetic correlations of direct additive genetic effect between litter size (TNB, NBA) and teat numbers were low (-0.18 and -0.14, respectively). However, genetic correlations of maternal effect between litter size (TNB, NBA) and teat numbers were a little bit higher than those of direct additive genetic effect (0.08 and 0.16, respectively).

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.