• 한국습지학회지
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• 제15권2호
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• pp.233-250
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• 2013

강수지표의 변화시점(change point) 분석을 이용하여 기후의 특성이 점진적 또는 급진적으로 변화하는지에 대하여 조사하였다. 강수지표를 크게 총량(amount), 극치(extremes)와 빈도(frequency)로 구분하였고, 각각의 지수를 RIA(Rainfall Index for Amount), RIE(Rainfall Index for Extremes)와 RIF(Rainfall Index for Frequency)로 정의하였다. 계산된 강수지표의 시간에 따른 변화를 알아보기 위하여 BCP(Bayesian Change Point)를 적용하였다. 분석 결과, 남한지역의 강수지표는 연 강우일수와 200년 빈도 확률 강수량을 제외하고는 모두 증가 하는 것으로 확인되었다. RIA는 울릉도 지점에서 변화지점의 유의성에 대해 매우 명확한 모습을 보였고 RIE는 제천, 서귀포와 구미 등에서 비교적 유의한 결과가 확인되었다. 또한, 1990년대 이후에 변동지점의 개수가 증가하고 있으며, 변동지점의 횡적인 폭 또한 비교적 넓어지고 있었다. 이러한 사실에 근거하여 볼 때 강수에 대한 정상성 가정에 대한 재고가 필요하리라 판단되었다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 추계학술대회
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• pp.57-72
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• 2003

This article provides integrated neural network models for the interest rate forecasting using change-point detection. The model is composed of three phases. The first phase is to detect successive structural changes in interest rate dataset. The second phase is to forecast change-point group with data mining classifiers. The final phase is to forecast the interest rate with BPN. Based on this structure, we propose three integrated neural network models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported neural network model, (2) case based reasoning (CBR)-supported neural network model and (3) backpropagation neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. For interest rate forecasting, this study then examines the predictability of integrated neural network models to represent the structural change.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.641-651
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• 2003

This study suggests the hybrid models for interest rate forecasting using structural changes (or change points). The basic concept of this proposed model is to obtain significant intervals caused by change points, to identify them as the change-point groups, and to reflect them in interest rate forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in the U. S. Treasury bill rate dataset. The second phase is to forecast the change-point groups with data mining classifiers. The final phase is to forecast interest rates with backpropagation neural networks (BPN). Based on this structure, we propose three hybrid models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported model, (2) case-based reasoning (CBR)-supported model, and (3) BPN-supported model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. For interest rate forecasting, this study then examines the prediction ability of hybrid models to reflect the structural change.

• 산업기술연구
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• 제35권
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• pp.23-30
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• 2015

In recent, the various methods to predict the hydrological impacts due to climate change have been developed and applied. Especially, the variability of the meteorological factors such as rainfall, temperature, and evaporation can impact on the ecosystem in a basin. The variability caused by climate change on the meteorological factors can be divided by a gradual and abrupt change. Therefore, in this study, the gradual change is detected by simple linear regression and Mann-Kendall trend test. Also, the abrupt change is detected by Bayesian change point analysis. Finally, the result using these methods can identify the meteorological threats in the Cheongmicheon basin.

• Communications for Statistical Applications and Methods
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• 제26권6호
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• pp.539-556
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• 2019

This paper derive a method to solve change point regression problems via a process for obtaining consequential results using properties of a difference-based intercept estimator first introduced by Park and Kim (Communications in Statistics - Theory Methods, 2019) for outlier detection in multiple linear regression models. We describe the statistical properties of the difference-based regression model in a piecewise simple linear regression model and then propose an efficient algorithm for change point detection. We illustrate the merits of our proposed method in the light of comparison with several existing methods under simulation studies and real data analysis. This methodology is quite valuable, "no matter what regression lines" and "no matter what the number of change points".

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.185-193
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• 2002

The purpose of this paper is to suggest a method for detecting the linear regression change-points or variance change-points in regression model by the combination of Schwarz information criteria. The advantage of the suggested method is to detect change-points more detailed when one compares the suggest method with Chen (1998)'s method.

• 한국지구과학회:학술대회논문집
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• 한국지구과학회 2010년도 춘계학술발표회 논문집
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• pp.73-73
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• 2010

The purpose of this study is to analyze illustrations, contents, and experiment in 6 kinds of science textbook from the 9th grade covering the phase change of the Moon (on the phase change of the Moon in six 9th grade science textbook) and to suggest coherent and effective contents and frame of the science textbook. Hence, the researcher decided the study problem. The study problems are as follows; 'Are the illustrations in the science textbook presented to help understand the phase change of the Moon depending on the position of the observer?', 'Does the contents of the book clearly mention the phase change of the Moon?', 'Can students understand the phase change of the Moon through the experiments in the science textbook?', 'Do illustrations, contents, and experiment of the science textbook consistently explain phase change of the Moon?'. 10 persons (9graduate students including the researcher) took part in this study. All things unanimously agreed upon by all participants were reflected in the results. The results are as follows. First, the universe observer's view point is mixed with the earth observer's view in illustration of these science textbook regarding the phase change of the Moon. Moreover, illustrations of some textbooks are presented with such words as 'sunrise', 'midnight' and consequently contain too much contents. Second, the contents of the science textbook concerning the phase change of the Moon is not described clearly. In addition, they don't give clear and detailed explanations for the reason of the phase change of the Moon. Third, all of the textbooks, except one textbook, describe the experiment regarding the phase change of the Moon with the earth observer's view point but don't specifically mention that the view point is that of the earth observer's view point. Fourth, illustrations, contents, and experiments in the science textbook don't coherently explain the phase change of the Moon. In addition, it is confirmed through the process of the result analysis that the described contents in the science curriculum is not well constructed or logical.

• 품질경영학회지
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• 제30권4호
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• pp.78-85
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• 2002

The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper, a new test statistic for testing whether or not the mean residual life changes its trend is developed. It is assumed that neither the change point nor the proportion at which the trend change occurs is known. The asymptotic null distribution of test statistic is established and asymptotic critical values of the asymptotic null distribution is obtained. Monte Carlo simulation is used to compare the proposed test with previously known tests.

• Asian Pacific Journal of Cancer Prevention
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• 제17권sup3호
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• pp.5-10
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• 2016

Breast cancer, the second cause of cancer-related death after lung cancer and the most common cancer in women after skin cancer, is curable if detected in early stages of clinical presentation. Knowledge as to any age cut-off points which might have significance for prognostic groups is important in screening and treatment planning. Therefore, determining a change-point could improve resource allocation. This study aimed to determine if a change point for survival might exist in the age of breast cancer diagnosis. This study included 568 cases of breast cancer that were registered in Breast Cancer Research Center, Tehran, Iran, during the period 1986-2006 and were followed up to 2012. In the presence of curable cases of breast cancer, a change point in the age of breast cancer diagnosis was estimated using a mixture survival cure model. The data were analyzed using SPSS (versions 20) and R (version 2.15.0) software. The results revealed that a change point in the age of breast cancer diagnosis was at 50 years age. Based on our estimation, 35% of the patients diagnosed with breast cancer at age less than or equal to 50 years of age were cured while the figure was 57% for those diagnosed after 50 years of age. Those in the older age group had better survival compared to their younger counterparts during 12 years of follow up. Our results suggest that it is better to estimate change points in age for cancers which are curable in early stages using survival cure models, and that the cure rate would increase with timely screening for breast cancer.

• Journal of the Korean Data and Information Science Society
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• 제27권5호
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• pp.1253-1262
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• 2016

위험률에 변화점이 존재할 경우 위험률 변화점에 대한 추정 정확한 모수 추정을 위해 매우 필요하다. 본 연구에서는 한 개 위험률 변화점이 존재하는 경우 위험률의 변화점 추정량에 대한 비교 연구를 수행하였다. 우도함수에 기반한 모수적 방법인 Matthews와 Farewell (1982) 위험률 변화점 추정량과 Nelson-Aalen 누적 위험률에 기반한 비모수적 방법의 Zhang 등 (2014) 위험률 변화점 통계량을 고찰하여 특성을 파악하였다. 모의실험에서 지수분포를 따르는 생존데이터에 대해 위험률 변화점이 한 개 있는 경우 중도절단이 없는 경우와 중도절단이 있는 경위험률 추정량의 능력을 평균제곱오차를 계산하여 비교하였다. 실제 데이터에 대한 적용으로 백혈병 생존데이터와 원발성 담백증 경화 생존데이터에 대해 위험률 변화점을 추정하고 비교해 보았다.