• Journal of the Korean Statistical Society
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• 제30권3호
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• pp.387-406
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• 2001

Adaptive estimators for a class of nonlinear time series models has been proposed by several authors. Koul and Schick(1997) proposed the adaptive estimators without sample splitting for location-type time series models. They also showed by simulation that the adaptive estimators without sample splitting have smaller mean squared errors than those of the adaptive estimators with sample splitting. the present paper generalized the result in a case of location-scale type nonlinear time series models by simulation.

• 응용통계연구
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• 제33권4호
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• pp.467-482
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• 2020

본 논문은 이분산성을 갖는 위치-척도 시계열 모형에서 모수의 변화에 대한 모니터링 절차를 연구한다. 모니터링 절차에서 수정된 잔차의 누적합을 이용한 탐지기를 소개하고 귀무가설과 대립가설 하에서 각각 모니터링 절차에 대한 점근적 성질을 규명한다. 그리고 모의실험과 사례 분석을 통하여 제안한 모니터링 방법의 성능이 우수함을 확인한다.

• Communications for Statistical Applications and Methods
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• 제30권4호
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• pp.369-388
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• 2023

In this paper, we develop the two-step procedure that detects and estimates the position of structural changes for multivariate nonstationary time series, either on mean parameters or second-order structures. We first investigate the presence of mean structural change by monitoring data through the aggregated cumulative sum (CUSUM) type statistic, a sequential procedure identifying the likely position of the change point on its trend. If no mean change point is detected, the proposed method proceeds to scan the second-order structural change by modeling the multivariate nonstationary time series with a multivariate locally stationary Wavelet process, allowing the time-localized auto-correlation and cross-dependence. Under this framework, the estimated dynamic spectral matrices derived from the local wavelet periodogram capture the time-evolving scale-specific auto- and cross-dependence features of data. We then monitor the change point from the lower-dimensional approximated space of the spectral matrices over time by applying the dynamic principal component analysis. Different from existing methods requiring prior information on the type of changes between mean and covariance structures as an input for the implementation, the proposed algorithm provides the output indicating the type of change and the estimated location of its occurrence. The performance of the proposed method is demonstrated in simulations and the analysis of two real finance datasets.

• Structural Monitoring and Maintenance
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• 제6권3호
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

• Wind and Structures
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• 제26권3호
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• pp.129-146
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• 2018

Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

• The Journal of Asian Finance, Economics and Business
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• 제7권6호
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• pp.19-27
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• 2020

This research investigates the determinants of investment capital size in Vietnam's small and medium-sized firms. The study employs a sample of 458 small and medium-sized enterprises in the country. The study is based on data collects in the areas of Hanoi, Bac Can, Buon Ma Thuot and Pleiku Provinces at time series data of October 2019. This study also identifies the factors that affect the size of investment capital in medium and small-sized enterprises in Vietnam. Data are processed via STATA 14.0 and SPSS 20.0 software. The research results indicate that (1) business lines, (2) import and export business, (3) type of business registration, (4) business location, (5) operating time, and (6) the percentage of the organization's capital contribution are factors that impact on the size of the investment capital of the business. Business line and business location have negative impacts on investment capital size. The operating time, the percentage of the organization's capital contribution, import and export business, and the type of business registration have positive impacts on investment capital size. In addition, the findings of this study also suggest that the operation time has the highest impact on investment capital size of the small and medium-sized firms in Vietnam.

• 국토계획
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• 제54권3호
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• pp.75-90
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• 2019

As the 24-hour society arrives, human activities in daytime and nighttime urban spaces are changing drastically, and the need for new urban management policies is steadily increasing. This study analyzes the types and characteristics of Seoul's human dynamics using location-based big data and the results are summarized as follows. First, the pattern of human dynamics in Seoul repeats itself every 7 days. Second, the types of human dynamics in Seoul can be classified into five types, and each of type has its own unique time-series and local characteristics. Third, the degree of match between human dynamics and zoning system in urban planning legislation was highest in 'Type 1' residence pattern and low in other types. The following implications can be drawn from these results. First, This paper examined the methodology of analyzing the regional characteristics of Seoul through the human dynamics and obtained meaningful results. Second, This paper can derive reliable and objective pattern analysis results using Big data that reflect the overall population characteristics. Third, the scale of night-time activity in the urban space of Seoul was understood, and its distribution, patterns and characteristics identified.

• 한국실내디자인학회논문집
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• 제41호
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• pp.137-145
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• 2003

This research analyzed the space scheme in connection with complexity, one of the new changes in the discount stores, and has a goal of predicting the direction of space scheme in the upcoming complexity era. The research was conducted in the following way. Firstly, this researcher tried to grasp what kinds of changes were required in the overall distribution industry socially and economically. Secondly, the characteristic and situation of discount stores were scrutinized. Thirdly, the domestic stores' complexity status was classified and types of those were elicited. Fourthly, the time-series change and use were analyzed. The result of this analysis reveals that the types of complexity can be divided by location and adjustment to environmental changes. The time-series analysis shows that total operating area, the number of parked cars and the tenant ratio have increased dramatically in 2000 and 2003. And, according to the correlation analysis between factors, the tenant ratio has, a strong correlation with other two factors. Self-complexity takes the basic form of living facilities and complexity with other facilities is combined with other cultural, sales, educational and administrative ones. Mass-complexity is merged with the stadiums, parks or station sites. As you've seen, the concept of complex shopping mall for the realization of one stop shopping and convenience will continue in the days to come. It is desirable that the study on the large-scale shopping spaces will be conducted continually for the preparedness of future life style.

• 한국습지학회지
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• 제14권3호
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• pp.341-352
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• 2012

본 연구의 목적은 미래 확률강우량을 통계적으로 전망하고 홍수취약도 모형을 통하여 미래 서울 지역의 홍수취약도를 정량적으로 가늠해 보는 것이다. 비정상성(non-stationarity)을 고려한 확률강우량 전망을 위하여 서울 지점의 연최대 일강우량을 초기 30년 자료 이후로 1년씩 누적하며 General Extreme Value (GEV) 분포의 매개변수를 추정하였다. 시간 대 위치, 규모 및 형상 매개변수의 선형정도를 비교하여 시간에 따른 위치 매개변수의 선형회귀식을 구성하고, 선형회귀분석에 의한 위치 매개변수를 이용하여 2030년의 확률강우량을 산정하였다. 이 확률강우량을 장옥재와 김영오 (2009)가 제안한 홍수취약도 분석의 모델의 입력자료로 하여, 2030년 서울지역의 홍수취약도를 평가하였다. 연구 결과, 2030년에 재현기간 100년의 강우가 발생한다면 현재에 비해 지역 평균 5 %정도 취약도가 증가하리라 전망되었다.

• 한국농림기상학회지
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• 제10권2호
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• pp.35-46
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• 2008

토양수분은 사면에서의 수문학적 과정의 가장 중요한 요소이며, 불포화대에서의 흐름을 결정하는 중요요소이다. 본 연구는 전이함수모형을 이용하여 토양수분의 시간적 공간적 분포 양상을 인지하고자 한다. 이를 위하여, 광릉 수목원 슈퍼사이트 원두부 소유역 내에서 TDR을 이용하여 2시간 간격으로 연속 측정한 10cm 깊이의 토양수분 결과를 전이함수를 통하여 분석하였다. 강우 자료를 입력변수로, 지표면으로부터 10cm 깊이의 실측 토양수분 자료를 출력변수로 선정하여 단일 입출력 전이함수를 전개하였다. 토양수분의 계절적인 변화를 분석하기 위해 5월과 9월의 전이함수를 비교하였다. 시계열 전이 함수는 크게 자료의 전처리, 모형구조의 규명, 후보 모형군의 구성, 모수추정, 모형진단 등의 과정을 통해서 전개되며 10cm 깊이의 토양수분과 강우의 상관관계를 보여준다. 도출한 전이함수 시계열 모형에서 10cm 깊이의 토양수분은 강우에 의한 영향이 지배적이었으며, 지점별 경사에 따라 토양수분의 변동성이 크게 차이를 나타내지 않았다. 이는 10cm 깊이의 토양수분 변동량은 각 지점의 경사보다 강우에 의한 반응이 우세하다는 것을 시사한다. 계절별로 상이한 모의 결과는 식생의 활동이 활발한 5월에는 식생이 토양수분 이동에 많은 영향을 미치며 식생이 토양수분을 해석하는데 중요한 변수로 작용함을 나타낸다. 본 연구 결과는 광릉 산림과 같은 복잡 경관에서 토양수분의 분포를 이해하는 기반자료가 될 것으로 기대된다.