• Journal of Wetlands Research
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• v.15 no.2
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• pp.233-250
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• 2013

Gradually or radically change how the characteristics of the climate characteristic using change point analysis for the precipitation indicators were investigated. Significantly the amount, extreme and frequency were separated by precipitation indicators, each indicator RIA(Rainfall Index for Amount), RIE(Rainfall Index for Extremes) and RIF(Rainfall Index for Frequency) was defined. Bayesian Change Point was applied to investigate changing over time of precipitation indicators calculated. As the result of analysis, precipitation indicators in South Korea was found to recently increase all indicators except for the annual precipitation days and 200-yr precipitation. RIA revealed that there was a very clear point of significance for the change in Ulleungdo, Relatively significant results for RIE were identified in Gumi, Jecheon and Seogwipo. Also, since the 1990s, an increase in the number of variation points, and the horizontal width of the fluctuation point was being relatively wider. Based on these results, rethink the precipitation on the assumption of stationarity was judged necessary.

• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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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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• v.14 no.3
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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.

• Journal of Industrial Technology
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• v.35
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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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• v.26 no.6
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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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• v.13 no.2
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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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• 2010.04a
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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.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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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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• v.17 no.sup3
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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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• v.27 no.5
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• pp.1253-1262
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• 2016

When there exists a change-point in hazard function, it should be estimated for exact parameter or hazard estimation. In this research, we compare the hazard change-point estimators. Matthews and Farewell (1982) parametric change-point estimator is based on the likelihood and Zhang et al. (2014) nonparametric estimator is based on the Nelson-Aalen cumulative hazard estimator. Simulation study is done for the data from exponential distribution with one hazard change-point. The simulated data generated without censoring and the data with right censoring are considered. As real data applications, the change-point estimates are computed for leukemia data and primary biliary cirrhosis data.