• Journal of the Korean Statistical Society
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• 제25권1호
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• pp.123-131
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• 1996

The problerm of testing for a constant mean is considered. A Kolmogorov-Smirnov type test using the sample Fourier coefficients is suggested and its asymptotic distribution is derived. A simulation study shows that the proposed test is more powerful than the cusum type test when there is more than one change-point or there is a cyclic change.

• 응용통계연구
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• 제25권6호
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• pp.999-1008
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• 2012

A Bayesian multiple change-point model for small data is proposed for multivariate means and is an extension of the univariate case of Cheon and Yu (2012). The proposed model requires data from a multivariate noncentral $t$-distribution and conjugate priors for the distributional parameters. We apply the Metropolis-Hastings-within-Gibbs Sampling algorithm to the proposed model to detecte multiple change-points. The performance of our proposed algorithm has been investigated on simulated and real dataset, Hanwoo fat content bivariate data.

• Communications for Statistical Applications and Methods
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• 제29권1호
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• pp.127-150
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• 2022

We discuss multiple change-point estimation as edge detection in piecewise smooth functions with finitely many jump discontinuities. In this paper we propose change-point estimators using concentration kernels with Fourier coefficients. The change-points can be located via the signal based on Fourier transformation system. This method yields location and amplitude of the change-points with refinement via concentration kernels. We prove that, in an appropriate asymptotic framework, this method provides consistent estimators of change-points with an almost optimal rate. In a simulation study the proposed change-point estimators are compared and discussed. Applications of the proposed methods are provided with Nile flow data and daily won-dollar exchange rate data.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• 품질경영학회지
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• 제16권2호
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• pp.68-81
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• 1988

Testing procedures for a detection of change point in the regression model with correlated errors are discussed. A Bayesian approach is adopted and applied to a regression model with errors following an AR(1) model.

• Journal of the Korean Statistical Society
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• 제35권1호
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• pp.1-23
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• 2006

In this paper we consider an estimation of the discontinuous variance function in nonparametric heteroscedastic random design regression model. We first propose estimators of the change point in the variance function and then construct an estimator of the entire variance function. We examine the rates of convergence of these estimators and give results for their asymptotics. Numerical work reveals that using the proposed change point analysis in the variance function estimation is quite effective.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 추계 학술발표회 논문집
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• pp.103-108
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• 2002

We consider an estimation of discontinuous variance function in nonparametric heteroscedastic random design regression model. We first propose estimators of a change point and jump size in variance function and then construct an estimator of entire variance function. We examine the rates of convergence of these estimators and give results on their asymptotics. Numerical work reveals that the effectiveness of change point analysis in variance function estimation is quite significant.

• International Journal of Reliability and Applications
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• 제3권2호
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• pp.91-98
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• 2002

A class of life distributions, whose mean residual life keeps stable at its earlier phase and then starts to decrease in time, is proposed to model the life of an element haying survived its burn-in. A strongly consistent estimator and a nonparametric testing procedure are developed to locate the occurrence of the change-point of the mean residual life. Finally, some numerical simulations are employed to be an illustration as well.

• 응용통계연구
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• 제11권1호
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• pp.163-175
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• 1998

위험률 변화점모형에서 특별한 함수형이나 분포함수에 대한 가정을 하지 않는 일반적인 모형을 고려하였다. 이러한 모형은 지금까지 주로 다루어 왔던 상수항 위험률의 변화점모형뿐만 아니라 여러 유형의 변화점모형을 내포한다. 중도절단된 자료하에서 위험률 변화점에 관한 모수적 모형을 가정하지 않고 변화점 이전과 이후의 넬슨(Nelson) 누적위험함수 추정량의 기울기 차를 이용하여 추정량을 제안하고, 그의 점근적 성질을 규명한다. 붓스트랩 추정량의 일치성과 점근분포를 유도하고, 몇가지 분포함수의 경우에 몬테칼로 모의실험을 통해 제안된 방법의 경험적 성질을 살펴보았다. 또한, 심장병 이석환자의 생존시간 자료를 통해 변화점을 추정하고 추정량의 붓스트랩 분포를 구하였다.

• 경영과학
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• 제18권1호
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• pp.119-133
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• 2001

It is important to find the equilibrium level of real interest rate for it affects real and financial sector of economy. However, it is difficult to find the equilibrium level because like the most macroeconomic model the real interest model has parameter instability problem caused by structural change and it is supported by various theories and definitions. Hence, in order to cover these problems structural change detection model of real interest rate is developed to combine the real interest rate equilibrium model and the procedure to detect structural change points. 3 equations are established to find various effects of other interest-related macroeconomic variables and from each equation, structural changes are found. Those structural change points are consistent with common expectation. Oil Crisis (December, 1987), the starting point of Economic Stabilization Policy (January, 1982), the starting point of capital liberalization (January, 1988), the starting and finishing points of Interest deregulation (January, 1992 and December, 1994), Foreign Exchange Crisis (December, 1977) are detected as important points. From the equation of fisher and real effects, real interest rate level is estimated as 4.09% (October, 1988) and dependent on the underlying model, it is estimated as 0%∼13.56% (October, 1988), so it varies so much. It is expected that this result is connected to the large scale simultaneous equations to detect the parameter instability in real time, so induces the flexible economic policies.