• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.343-352
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• 2018

We can use quantile regression and expectile regression analysis to estimate trends in extreme regions as well as the average trends of response variables in given explanatory variables. In this paper, we compare the performance between the parametric and nonparametric methods for expectile regression. We introduce each estimation method and analyze through various simulations and the application to real data. The nonparametric model showed better results if the model is complex and difficult to deduce the relationship between variables. The use of nonparametric methods can be recommended in terms of the difficulty of assuming a parametric model in expectile regression.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.73-94
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• 2003

In general, the interest rate is forecasted by the parametric method which assumes the interest rate follows a certain distribution. However the method has a shortcoming that forecasting ability would decline when the interest rate does not follow the assumed distribution for the stochastic behavior of interest rate. Therefore, the nonparametric method which assumes no particular distribution is regarded as a superior one. This paper compares the interest rate forecasting ability between the two method for the Monetary Stabilization Bond (MSB) market in Korea. The daily and weekly data of the MSB are used during the period of August 9th 1999 to February 7th 2003. In the parametric method, the drift term of the interest rate process shows the linearity while the diffusion term presents non-linear decline. Meanwhile in the nonparametric method, both drift and diffusion terms show the radical change with nonlinearity. The parametric and nonparametric methods present a significant difference in the market price of interest rate risk. This means in forecasting the interest rate and the market price of interest rate risk, the nonparametric method is more appropriate than the parametric method.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.398-398
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• 2021

섬진강은 한국 주요 5대강 중 하나로 유량 변동계수가 가장 크다. 이로 인해, 극심한 가뭄이나 홍수의 발생 확률이 높을 뿐만 아니라, 가뭄에서 홍수 또는 홍수에서 가뭄으로 갑작스러운 극한 수문 기상 변화가 일어날 수 있다. 수자원의 안정적인 확보와 수재해로 인한 피해를 최소화하기 위한 수자원 관리와 장기적 수문분석이 필요하다. 이에 본 연구에서는 섬진강 유역의 수문 관측소(56개)에서 10년 이상 장기 관측된 일유량 자료(1997년~2020년)를 이용하여 비모수 검정 방법을 통한 추세 분석과 변동점을 탐색하였다. 우선, 일유량 관측 자료를 이용하여 누락된 일유량 관측값으로 생겨날 수 있는 불확실성을 배제하기 위해 관측 기간 중 누락된 일유량 관측값들의 월별 비율을 조사하였다. 그리고 월별 일유량 관측값 누락이 없는 관측소들의 월평균 하천 유량 값으로 연평균 하천 유량 값을 계산하였다. 관측 기간 동안 결측된 값이 없는 28개의 관측소를 대상으로 비모수 검정 방법을 통한 연별 추세 분석(Mann-Kendall Test)과 변동점 탐색(Pettitt Test)을 하였다. 연별 추세 분석 경우 28개의 관측소 중 8개의 관측소에서 통계적으로 의미 있는 추세(신뢰도> 99%)가 탐지되었다. 이들 중 3개의 관측소에서는 증가하는 추세를 보였고 5개의 관측소에서 감소하는 추세가 보였다. 7개의 관측소에서는 통계적으로 의미가 있는 변동점도 탐색되었고 그 변동점이 탐색된 연도는 2011년(4개), 2012년(3개)로 나타났다. 계절적 추세 분석에서는 28개의 관측소 중 각각 봄(MAM) 11개, 여름(JJA) 11개, 가을(SON) 9개, 겨울(DJF) 11개 관측소에서 통계적 추세(신뢰도> 99%)가 탐지되었다. 또한 봄 17개, 여름 7개, 가을 18개, 겨울 18개 관측소에서 변동점이 탐색되었고, 그 연도는 관측소마다 달랐다. 이러한 유량의 추세와 변동점의 원인(기후적/인위적 요소)을 더욱 잘 이해하기 위해, 계절별 유량과 강수량의 상관관계 분석이 연구될 필요가 있다. 이러한 장기 수문기후학적 추세와 변동성에 대한 이해는 농업이 중요한 섬진강 유역의 수자원 관리와 기후변화에 선제대응 할 수 있는 기초를 마련할 것이다.

• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.83-100
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• 2019

This study, we conducted a non-parametric trend test (Seasonal Kendall tests, LOWESS) and Cross Correlation. We aimed to identify water quality trends using the weekly data for 9 variables (Water Temperature, EC, DO, BOD, COD, T-N, T-P, TOC and Chl-a) collected from 4 sites in the Paldang Lake from 2004.01 to 2016.12. According to the Seasonal Kendall test, Water temperature increased but EC, T-N and T-P decreased trend. LOWESS showed that BOD was gradually decreased from 2013 to 2016. but COD gradually increased between 2012 and 2016. As a result, it was confirmed that the period between 2012 and 2013 was a turning point in the increase of COD along with the decrease of BOD at all sites in Paldang Lake. Results of Cross Correlation showed that there was no time difference between all of Water variables and Sites. In this study, it is necessary to analyze the cause of the transition period and to monitoring the water quality more precisely for better water quality management in Paldang Lake.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.123-138
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• 2010

After selecting a group of women with premenstrual syndrome based on daily distress scores of 28 days, one needs to estimate threshold for the change of symptoms, which would be useful for the clinician's diagnosis in hospitals. However, a test of whether a change has occurred has to precede the estimation of the threshold. In this paper, we apply parametric and nonparametric testing methods to an example data obtained from a group of women. Nonparametric method does not assume any distributional form of distress scores and parametric testing method is based on the normal distributions of linear regression lines. Therefore, the optimal situation of both methods would be different and we will assess it with a simulation study.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.19-33
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• 2008

Linear regression method, proposed by Haseman and Elston(1972), for detecting linkage to a quantitative trait of sib pairs is a linkage testing method for a single locus and a single trait. However, multivariate methods for detecting linkage are needed, when information from each of several traits that are affected by the same major gene are available on each individual. Amos et al. (1990) extended the regression method of Haseman and Elston(1972) to incorporate observations of two or more traits by estimating the principal component linear function that results in the strongest correlation between the squared pair differences in the trait measurements and identity by descent at a marker locus. But, it is impossible to control the probability of type I errors with this method at present, since the exact distribution of the statistic that they use is yet unknown. In this paper, we propose a multivariate nonparametric trend test for detecting linkage to multiple traits. We compared with a simulation study the efficiencies of multivariate nonparametric trend test with those of the method developed by Amos et al. (1990) for quantitative traits data. For multivariate nonparametric trend test, the results of the simulation study reveal that the Type I error rates are close to the predetermined significance levels, and have in general high powers.

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.689-696
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• 2005

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the Kappa(2) reliability model, which can capture the nomotonic decreasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on sum of the squared errors and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing two parameter of the Kappa distribution, was employed. This analysis of failure data compared with the Kappa model and the existing model using arithmetic and Laplace trend tests, bias tests is presented.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.45-53
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• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the $x^2$ reliability model, which can capture the increasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing shape parameter of the $x^2$ distribution using the degree of freedom, was employed. This analysis of failure data compared with the $x^2$ model and the existing model using arithmetic and Laplace trend tests, Kolmogorov test is presented.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1081-1091
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• 2010

Clinical trials are often carried out as multi-center studies because the patients enrolled for a trial study are very limited in one particular hospital. In these circumstances, the use of an ordinary Jonckheere (1954) and Terpstra (1952) test for testing trend among several independent treatment groups is invalid. We propose a the stratified Jonckheere-Terpstra test based on van Elteren (1960)'s stratified test of Wilcoxon (1945) statistics and an application of our method is demonstrated through example data. A simulation study compares the efficiency of stratified and unstratified Jonckheere-Terpstra trend tests.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1610-1614
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• 2010

최근 기후변화로 인한 우리나라 호우일수(80mm이상/일)의 증가, 강우강도의 증가에 따른 개별 홍수에 의한 재해규모가 증가하고 있는 현실에서 전통적인 빈도해석기법을 이용한 설계 강우량 산정과 적용에는 한계가 있다. 그러나 우리나라에서는 아직도 비정상성을 고려한 빈도해석기법이 표준화되어 있지 않고 있으며, 전통적인 빈도해석기법에 의존하여 실무에 활용되고 있는 실정이다. 따라서 본 연구에서는 기후변화에 따른 우리나라 강수 극치사상의 변동특성을 분석하고자 하였다. 연구 대상지역으로 기상청에서 운영하는 기상관측소 중에서 90년 이상의 장기 강수자료가 구축되어 있는 서울, 부산, 인천, 대구, 강릉, 목포 등 여섯 곳을 선정하였다. 선정된 6개 기상관측소의 강수자료를 이용하여, 비모수적 선형추세분석기법인 Mann-Kendall 검정을 수행하였다. 본 연구를 통하여 얻어진 결과는 우리나라의 전통적인 설계 강우량 산정기법 개선에 대한 필요성 인식과 설계 강우량 산정에 대한 새로운 접근방향 제시와 이에 따른 제도적 개선 요구에 대한 기초자료로 활용될 수 있을 것으로 판단된다.