• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.27-40
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• 2001

The purpose of this study is to test a multiple change point in the regression model with the passage of time, using the estimated residual variance figure suggested by Gasser, Sroka and Jennen - Steinmez (GSJS). As a result of the simulation, it is showed that there is a jump change of the estimated residual variance figure at that time of change point. The way to analyse a intuitive multiple change point through graphics is more effective and accurate than any other existing ways.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.653-664
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• 2000

The problem of inference about the unknown change-point with a change in mean is considered. We suggest a nonparametric change-point estimator using window and prove its consistency when the errors are from the distribution with the mean zero and the common variance. a comparison study is done by simulation on the mean, the variance, and the proportion of matching the true change-points.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.753-763
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• 2002

When there is one change-point in the hazard rate model, a change-point estimator with the partial score process is suggested and compared with the previously developed estimators. The limiting distribution of the partial score process we used is a function of the Brownian bridge. Simulation study gives the comparison of change-point estimators.

• 한국데이터정보과학회:학술대회논문집
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• 2004.10a
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• pp.25-32
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• 2004

In this study, we use various change-point detection methods to detects Korea economic crisis of 1997, and then compares their performance. In change-point detection method, there are three major categories: (1) the parametric approach, (2) the nonparametric approach, and (3) the model-based approach. Through the application to Korea foreign exchange rate during her economic crisis, we compare the employed change-point detection methods and, furthermore, determine which of them performs better.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.585-592
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• 2004

This study detects Korea economic crisis of 1997 using various change-point detection methods and then compares their performance. In change-point detection method, there are three major categories: (1) the parametric approach, (2) the nonparametric approach, and (3) the model-based approach. Through the application to Korea foreign exchange rate during her economic crisis, we compare the employed change-point detection methods and, furthermore, determine which of them performs better.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.75-86
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• 2002

We consider the problem of estimating the change-point in mean change model with one change-point. Gombay and Huskova(1998) derived a class of change-point estimators with the score function of rank. A change-point estimator with the log score function of rank is suggested and is shown to be involved in the class of Gombay and Huskova(1988). The simulation results show that the proposed estimator has smaller rose, larger proportion of matching the true change-point than the other estimators considered in the experiment when the change-point occurs in the middle of the sample.

• Communications for Statistical Applications and Methods
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• v.1 no.1
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• pp.10-19
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• 1994

We study the change-point problem in the context of system reliability models. The maximum likelihood estimators are obtained based on the Jelinski and Moranda model. To find the approximate distribution of the change-point estimator, we suggest of parametric bootstrap method in which the estimators are substituted in the assumed model. Through an example we illustrate the proposed method.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.423-432
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• 2012

This paper is concerned with the detection of multiple change-points in linear regression models. The proposed procedure relies on the local estimation for global change-point estimation. We propose a multiple change-point estimator based on the local least squares estimators for the regression coefficients and the split measure when the number of change-points is unknown. Its statistical properties are shown and its performance is assessed by simulations and real data applications.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.467-478
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• 1999

This paper deals with the problem of change-point estimation where there is one level change in location with iid errors. A change-point estimator using rank average is proposed with the proof of its consistency. A comparison study of various change-point estimators is done by simulation on the mean the proportion and the variance when the errors are from the normal and the double exponential distributions.

• 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.