• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.205-223
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• 2021

In this paper, we study a method to determine the existence of unit roots by using the adaptive lasso. The previously proposed method that applied the adaptive lasso to the original time series has low power when there is an unknown trend. Therefore, we propose a modified version that fits the ADF regression model without deterministic component using the adaptive lasso to the detrended series instead of the original series. Our Monte Carlo simulation experiments show that the modified method improves the power over the original method and works well in large samples.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.586-590
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• 2010

In this paper we formally define the linear detrending subsequence matching and propose its efficient index-based solution. To this end, we first present the notion of LD-windows. We eliminate the linear trend from a subsequence rather than each window itself and obtain LD-windows by dividing the subsequence into windows. Using the LD-windows we present a lower bounding theorem of the index-based solution and formally prove its correctness. Based on this lower bounding theorem, we then propose the index building and subsequence matching algorithms, respectively. Finally, we show the superiority of our index- based solution through experiments.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.865-877
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• 2009

While characterized initially as an urban-scale pollutant, ozone has increasingly been recognized as a regional and even global-scale phenomenon. The complexity of environmental data dynamics often requires models covering non-linearity. This study deals with modeling ozone with meteorology in Seoul area. The relationships are used to construct a nonlinear regression model relating ozone to meteorology. The model can be used to estimate that part of the trend in ozone levels that cannot be accounted for by trends in meteorology.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.573-589
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• 2023

In a piecewise linear trend model, the change points coincide with the mean change points of the first differenced time series. Therefore, by detecting the mean change points of the first differenced time series, one can estimate the change points of the piecewise linear trend model. In this paper, based on this fact, a method is proposed for detecting change points of the piecewise linear trend model using the simple moving average of the first differenced time series rather than estimates of the slope or residuals. Our Monte Carlo simulation experiments show that the proposed method performs well in estimating the number of change points not only when the error terms in the piecewise linear trend model are independent but also when they are serially correlated.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1479-1482
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• 2006

본 연구는 우리나라 강수자료 중 90년 이상의 자료를 보유한 지점(서울, 인천, 목포, 부산)에 대해서 변화도 분석과 Singular Spectrum Analysis(SSA)를 사용하여 자료의 주성분 및 주기성을 분석하였다. 각 자료의 변화도 분석결과 1907에서 2004년까지 98년간의 장기변화 중 선형추세에 의한 강우변화량은 23-11mm/mon 증가한다. 선형추세에 의한 년 강우변화량은 276-132mm/yr 이며 증분의 약 65%가 8월 증가량으로 과거 30년 강우분포는 7월에만 피크를 가지나 최근 30년의 강우분포는 7월과 8월에 비슷한 피크를 가지는 변화를 보일 뿐 아니라 지역에 따라 상이한 분포 양상을 보였다. 강우의 선형적 증가와 함께 변화폭도 증가하며 서울, 인천지역이 목포, 부산지역보다 큰 증가 양상을 보였다. 월 변화패턴과 선형추세 등 확정적 변화를 제거한 anomaly는 장기 변동과 각 달에 대해 다른 변동 폭을 가지는 noise의 합의 형태로 나타난다. Moving ave rage를 이용한 장기변동양상은 특정 주기를 가지지 않을 뿐만 아니라 변동 폭도 noise의 변동 폭에 비하여 미소하다. SSA결과 첫 번째 주성분이 전체변화의 1.7%이며 30번째 성분은 전체변화의 약 1% 정도로 장주기의 변화를 보였으나 전체자료에 비해 각 요소들이 설명하는 비중이 상당히 낮았다.

• Defense and Technology
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• no.2 s.252
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• pp.46-57
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• 2000

군 통신도 앞으로 상용에서의 이동통신 시스템이나 ATM(Asynchronous Transfer Mode), 위성통신과 같은 첨단 통신방식으로 발전하는 추세에 있으므로 전술제대 단위로 위치보고체계의 통신망을 구성한다면 상호운용성(Interoperability)면에서 중대한 문제점이 발생할 수 있다. 한편 장차전의 양상은 화력전, 입체 고속 기동전으로 가는 추세이며 기갑/기계화부대는 비선형 기동전의 주역으로서 적의 취약점을 포착하는 즉시 민첩한 기동전투력으로 종심공격을 실시하여 적에게 불리한 비선형의 전장을 적극적으로 조성하고 주도권을 행사하는 전술작전 능력을 발휘한다

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.163-175
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• 1997

Randomization of the run order within a block is a technique commonly employed by the experimenters of block designs to avoid biases in the estimates of the effects of interest. In practice, however the experimental responses are sometimes affected by the spatial or temporal position of the experimental units within a block. In such cases, it is preferable to use a systematic ordering of the treatments. It is often possible to find an ordering which will allow the estimation of treatment effects independently of any trend is known as a trend-free block designs. In many idustrial and agricultural experiments, treatments are applied to experimental units sequentially in time or space. This paper begins with a review of concepts and properties of trend-free designs. We, then devise algorithms to generate linear trend-free designs. We extend and modify the existing algorithm which is given by Bradley and Odeh(1988). Also, the algorithm which generate all possible linear trend-free designs in provided.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.371-384
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• 2022

The fused LASSO signal approximator (FLSA) can be applied to find change points from the data having piecewise constant mean structure. It is well-known that the FLSA is inconsistent in change points detection. This inconsistency is due to a total-variation denoising penalty of the FLSA. ℓ₁ trend filter, one of the popular tools for finding an underlying trend from data, can be used to identify change points of piecewise linear trends. Since the ℓ₁ trend filter applies the sum of absolute values of slope differences, it can be inconsistent for change points recovery as the FLSA. However, there are few studies on the inconsistency of the ℓ₁ trend filtering. In this paper, we demonstrate the inconsistency of the ℓ₁ trend filtering with a numerical study.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.945-957
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• 2009

Repeated measurement data among several treatments with a control is often used in the field of medicine study. In this paper, we suggest a method for comparison of the linear trend of responds followed time among several treatments with a control based on repeated measurement data. First, we estimate slope from each subject and generate samples using the slope estimated previous. And then, we test the difference among treatment with a control by ANOVA F test, Jonckheere-Terpstra test, updated control group procedure using generated samples. Monte Carlo Simulation is adapted to compare the power and experimental significance levels in various configuration.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.2
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• pp.67-77
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• 2016

This study developed synthetic regression diagram for analyzing the linear trend of sea surface height, temperature, and salinity around the Korean marginal seas. In situ observed data had been quality controlled and they were verified by EOF comparison with objective analyzed data. From the synthetic regression diagram, we confirmed similar linear regression values with those of previous studies, but additionally provided detailed regression rate of each 5 to 30 year for the total periods of 1983-2013. We expect that quantitative results presented by this study will be useful as standard reference numbers for relevant studies analyzing oceanic long-term trend.