• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.214-219
• /
• 2009

본 연구에서는 기후변동성 및 기후변화와 같은 외부충격을 극치수문사상 해석에 반영할 수 있는 비정상성 빈도해석 기법을 제안하고 서울지방 강수량에 대해서 검토를 실시하였다. 이러한 외부인자를 고려할 경우에 가장 큰 어려운 점은 극치분포의 매개변수를 효과적으로 추정하면서 동시에 불확실성을 정량화해야 한다는 점이다. 이러한 점에서 본 연구에서 제시한 Bayesian 방법은 상대적으로 우수한 해석 능력을 나타내고 있는 것으로 판단된다. 비정상성 빈도해석 기법을 서울지방 강수량에 선형경향성과 기후변화 영향을 고려하여 적용한 결과 현재에 비해 극치강수량에 발생 빈도가 크게 나타나는 특성을 보여주고 있다. 그러나 보다 신뢰성 있는 해석을 위해서 다양한 기상패턴 및 모형을 검토하는 것이 바람직 할 것으로 판단된다.

• The Korean Journal of Financial Management
• /
• v.12 no.1
• /
• pp.19-32
• /
• 1995

본 연구에서는 한국 주식시장에서의 주가행태가 Froot-Obstfeld(1991)의 내재적 거품모형(intrinsic bubbles model)과 일관성을 갖는지의 여부를 규명하기 위하여, 실질주가와 실질배당의 연별 및 분기별 시계열자료를 이용하여 실증분석을 실시하였다. 실증분석에 이용된 표본기간이 짧다는 점과 배당금 추정상의 잠재적인 오차가 본 연구의 실증분석 결과의 적극적인 해석을 제약하고 있으나, 전통적인 주가결정모형으로서의 현재가치모형은 일관성 있게 기각되고 있으며, 내재적 거품모형도 한국 주식시장에서의 주가행태와 일관성을 갖지 않는 것으로 나타났다. 이러한 실증분석 결과는 우리나라 주식시장에 다음과 같은 시사점을 주는 것으로 생각된다. 기업의 배당정책이 액면 배당 일변도로 이루어지는 우리나라의 실정에 비추어 볼 때 기본적 가치 (fundamentals)로서 배당을 중시하는 주가결정모형은 애초부터 한계를 가질 수 밖에 없을 것이다. 본 연구에서의 실증분석 결과가 배당의 비정상성(nonstationarity)에 의거한 주가결정 모형들을 기각하는 것 이라면, 앞으로의 연구과제는 우리나라의 주가행태와 일관성을 갖는 주가결정 모형을 개발하는 일이 될 것이다.

• Communications for Statistical Applications and Methods
• /
• v.7 no.2
• /
• pp.435-446
• /
• 2000

Statistical process control(SPC) and engineering process control(EPC) are two strategies for quality improvement that have been developed independently. EPC seeks to minimize variability by adjusting compensatory variables in order to make the process level close to the target, while SPC seeks to reduce variability by monitoring and eliminating causes of variation. One purpose of this paper is to propose the IMA(0,1,1) model as the in-control process model. For the out-of-control process model we consider two cases; one is the case with a step shift in the level, and the other is the case with a change in the nonstationarity. Another purpose is to suggest the use of an integrated process control procedure with adjustment and monitoring, which can consider the proposed process model effectively. An integrated control procedure will improve the process control activity significantly for cases of the proposed model, when compared to the procedure of using either EPC or SPC, since EPC will keep the process close to the target and SPC will eliminate special causes.

• Journal of the Korean Statistical Society
• /
• v.23 no.1
• /
• pp.167-178
• /
• 1994

To estimate coefficient matrix in autoregressive model, usually ordinary least squares estimator or unconditional maximum likelihood estimator is used. It is unknown that for univariate AR(p) model, unconditional maximum likelihood estimator gives better power property that ordinary least squares estimator in testing for unit root with mean estimated. When autoregressive model contains multiple unit roots and unconditional likelihood function is used to estimate coefficient matrix, the seperation of nonstationary part and stationary part of the eigen-values in the estimated coefficient matrix in the limit is developed. This asymptotic property may give an idea to test for multiple unit roots.

• The Journal of the Acoustical Society of Korea
• /
• v.8 no.1
• /
• pp.81-87
• /
• 1989

This paper discribes the method associated with modeling of Korean phonemes. Hidden Markov models(HMM's) may be viewed as an effective technique for modeling the inherent nonstationarity of speech signal. We propose a 3-state phoneme model to represent the sequentially changing characteristics of phonemes, i.e., transition-to-stationary-to-transition. Also we clarify that the duration of a phoneme is an important factor to have an effect in recognition accuracy and show that improvement in recognition rate can be obtained by using duration-dependent 3-state hidden Markov models.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.3
• /
• pp.697-707
• /
• 2017

In this paper, we propose a modified GARCH(p, q)-X model which is obtained by adding the exogenous variables to the modified GARCH(p, q) process. Some limiting properties are shown under various stationary and nonstationary exogenous processes which are generated by another process independent of the noise process. The proposed model extends the GARCH(1, 1)-X model studied by Han (2015) to various GARCH(p, q)-type models such as GJR GARCH, asymptotic power GARCH and VGARCH combined with exogenous process. In comparison with GARCH(1, 1)-X, we expect that many stylized facts including long memory property of the financial time series can be explained effectively by modified GARCH(p, q) model combined with proper additional covariate.

• The Korean Journal of Financial Management
• /
• v.24 no.2
• /
• pp.183-206
• /
• 2007

The price-dividend ratio is one of the most frequently used financial variables to predict long-horizon stock return. However, the persistency of the price-dividend ratio is found to cause the spuriousness of the stock return prediction regression. The stable relationship between the stock price and the dividend, however, seems to weaken after World War II and to experience structural break. In this paper, we identify a structural change in the cointegrating relationship between the log of the stock price and the log of the dividend. Confirming a structural break in 1962, we subdivide the sample and apply the fully modified estimator to correct for the nonstationarity of the regressor. With the subdivided sample, we exercise the nonparametric bootstrap procedure to derive the empirical distribution of the test statistics and fail to find return predictability in each subsample period.

• IEIE Transactions on Smart Processing and Computing
• /
• v.4 no.2
• /
• pp.103-109
• /
• 2015

In this paper, a novel method for the classification of term and preterm birth is proposed based on time-frequency analysis of electrohysterogram (EHG) using multivariate empirical mode decomposition (MEMD). EHG is a promising study for preterm birth prediction, because it is low-cost and accurate compared to other preterm birth prediction methods, such as tocodynamometry (TOCO). Previous studies on preterm birth prediction applied prefilterings based on Fourier analysis of an EHG, followed by feature extraction and classification, even though Fourier analysis is suboptimal to biomedical signals, such as EHG, because of its nonlinearity and nonstationarity. Therefore, the proposed method applies prefiltering based on MEMD instead of Fourier-based prefilters before extracting the sample entropy feature and classifying the term and preterm birth groups. For the evaluation, the Physionet term-preterm EHG database was used where the proposed method and Fourier prefiltering-based method were adopted for comparative study. The result showed that the area under curve (AUC) of the receiver operating characteristic (ROC) was increased by 0.0351 when MEMD was used instead of the Fourier-based prefilter.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.15-15
• /
• 2016

In South Korea, annual maximum precipitation often occurs in association with mature typhoons in the western Pacific and from summer monsoon rains. In addition, certain years have no significant typhoon activity. Therefore, the characteristics of frequency distributions differ between extreme typhoons and monsoon events. Those extremes are also influenced from climate conditions in a different way. Application of nonstationary frequency analysis to the AMP data combined with typhoon and monsoon events might not always be reasonable. Therefore, we propose a novel approach of nonstationary frequency analysis to integrate extreme events of AMP induced from two main sources such as typhoons and monsoon in the current study. In this way, we were able to model the nonstationarity of extreme events from tropical storms and monsoon separately.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.39 no.1
• /
• pp.165-174
• /
• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.