• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.915-928
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• 2011

The main purpose of this study is to understand the effects of hydroclimatic factors on annual actual evapotranspiration and to suggest the multiple linear regression (MLR) equations for the estimation of annual actual evapotranspiration from watershed. To accomplish this study purpose, 5 dam watersheds (Goesan dam, Seomjingang dam, Soyanggang dam, Andong dam, Hapcheon dam) were selected as study watersheds and annual actual evapotranspiration was estimated based on annual water balance analysis from each watershed. The estimated annual actual evapotranspiration from water balance analysis was used to evaluate the MLR equations. Furthermore, the possibility of the estimation of actual evapotranspiration using potential evapotranspiration equations (Penman equation, FAO P-M equation, Makkink equation, Preistley-Taylor equation, Hargreaves equation) was evaluated. It has turned out that it is not appropriate to use potential evapotranspiration for the estimation of actual evapotranspiration because the correlation between actual evapotranspiration and potential evapotranspiration is very low. The comparison of MLR equations with current actual evapotranspiration equations indicates that MLR equations can be used for the estimation of annual actual evapotranspiration. Furthermore, it has turned out that the effects of hydroclimatic factors on annual actual evapotranspiration from dam watersheds are different in each watershed; however, for all watersheds in common precipitation has turned out to be the most important climatic factor affecting on the estimation of annual actual evapotranspiration.

• KIPS Transactions on Computer and Communication Systems
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• v.13 no.1
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• pp.1-9
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• 2024

In the development and mass production of polymers, there are many uncontrollable variables. Even small changes in chemical composition, structure, and processing conditions can lead to large variations in properties. Therefore, Traditional linear modeling techniques that assume a general environment often produce significant errors when applied to field data. In this study, we propose a new modeling method (GPR-SEM) that combines Structural Equation Modeling (SEM) and Gaussian Process Regression (GPR) to study the Friction-Coefficient and Flexural-Strength properties of Polyacetal resin, an engineering plastic, in order to meet the recent trend of using plastics in industrial drive components. And we also consider the possibility of using it for materials modeling with nonlinearity.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.383-392
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• 2000

Since late 1970, methods of influence or sensitivity analysis for detecting influential observations have been studied not only in regression and related methods but also in various multivariate methods. If results of multivariate analyses sometimes depend heavily on a small number of observations, we should be very careful to draw a conclusion. Similar phenomena may also occur in the case of incomplete data. In this research we try to study such influential observations in multivariate statistical analysis of incomplete data. Case of principal component analysis is studied with a numerical example.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.1005-1013
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• 2017

In this paper, we investigate the performances of time series models to forecast irradiance that consider weather variables such as temperature, humidity, cloud cover and Global Horizontal Irradiance. We first introduce the time series models and show that regression ARIMAX has the best performance with other models such as ARIMA and multiple regression models.

• Ecology and Resilient Infrastructure
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• v.9 no.4
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• pp.269-281
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• 2022

The prediction of changes regarding the distribution of vegetation and plant species according to climate changes is important for ecosystem management. In this study, we attempted to develop an assessment method to evaluate the possibility of the potential distribution of warm-temperate woody plant species of East Asia in Korea. To begin with, a list of warm-temperate woody plants distributed in China and Japan, but not in Korea, was prepared, and a database consisting their global distribution and bioclimatic variables was constructed. In addition, the warm-temperate vegetation zone in Korea was delineated using the coldness index and relevant bioclimatic data were collected. After the exclusion of multicollinearity among bioclimatic variables using correlation analysis, mean temperature of the coldest quarter, mean temperature diurnal range, and annual precipitation were selected as the major variables that influence the distribution of warm-temperate plants. A multivariate environment similarity surfaces (MESS) analysis was conducted to calculate the similarity scores between the distribution of these three bioclimatic variables in the global distribution sites of the East Asian warm-temperate woody plants and the Korean warm-temperate vegetation zone. Finally, using stepwise variable-selection regression, the mean temperature of the coldest quarter and annual precipitation were selected as the main bioclimatic variables that affect the MESS similarity index. The mean temperature of the coldest quarter accounted for 88% of the total variance. For a total of 319 East Asian warm-temperate woody plant species, the possibility of their potential distribution in Korea was evaluated by applying the constructed multivariate regression model that calculates the MESS similarity index.

• Journal of Korea Port Economic Association
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• v.35 no.3
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• pp.61-72
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• 2019

In order to enhance the competitiveness of the container shipping industry and promote its development, based on the empirical analyses using multivariate time series models, this study aims to suggest a few strategies related to the dynamics of the container shipping market. It uses the vector autoregressive (VAR) and vector error correction (VEC) models as analytical methodologies. Additionally, it uses the annual trade volumes, fleets, and freight rates as the dataset. According to the empirical results, we can infer that the most exogenous variable, the trade volume, exerted the highest influence on the total dynamics of the container shipping market. Based on these empirical results, this study suggests some implications for ship investment, freight rate forecasting, and the strategies of shipping firms. Concerning ship investment, since the exogenous trade volume variable contributes most to the uncertainty of freight rates, corporate finance can be considered more appropriate for container ship investment than project finance. Concerning the freight rate forecasting, the VAR and VEC models use the past information and the cointegrating regression model assumes future information, and hence the former models are found better than the latter model. Finally, concerning the strategies of shipping firms, this study recommends the use of cycle-linked repayment scheme and services contract.

• The Korean Journal of Financial Studies
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• v.5 no.1
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• pp.135-164
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• 1999

본(本) 연구(硏究)는 Jobson(1982)의 주식(株式)의 수익율(收益率)이 정규분포(正規分布)를 할 경우에 다변량(多變量)의 통계학(統計學)을 이용하여 CAPM과 APM을 검증(檢證)하는 방법(方法)을 유도하였다. 이에따라 회귀분석(回歸分析)에 의한 검증방법(檢證方法)과 다변량(多變量)의 검증방법(檢證方法)을 제시하고 현실적으로 CAPM과 APM이 한국증권시장(韓國證券市場)에서 적용가능(適用可能)한가에 대한 실증적(實證的) 검증(檢證)을 실시하였다. 실증적(實證的) 검증(檢證)을 위하여 먼저 우리나라의 주식수익율자료(株式收益率資料)를 1980년 1월부터 1997년 6월까지의 월별자료(月別資料)에 의하여 11개 산업별(産業別) 분류작업을 통하여 산업별(産業別)포트폴리오를 구성하였다. 특히 APM의 경우에는 요인(要因)의 증가에 따라 APM이 한국증권시장에서 적용가능한가를 검증(檢證)하기 위하여 요인(要因)을 2개, 6개 그리고 10개까지 증가시켜 모형(模型)의 적합성(適合性)을 검증(檢證)하였다. 검증결과(檢證結果), CAPM과 APM모두 한국증권시장(韓國證券市場)에서 적용가능(適用可能)한 것으로 나타났다. 특히 APM의 경우에는 요인(要因)이 2개, 6개와 10개로 증가시 어떤 경우에도 적용가능한 것으로 나타났다. 이는 기대수익율(期待收益率)의 설명력을 높이기 위하여 몇 개의 가격화(價格化) 요인(要因)이 APM에 영향을 미치는 가를 연구하는 전통적인 검증방법(檢證方法)은 큰 의미가 없는 것으로 나타났다.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.675-693
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• 2011

We compare three Techniques control systems with The Investigate Study on the relation between Multivariate SPC and Autoregressed Algorithm. We also investigate Autoregressed Algorithm with relevant EWMA, CUSUM, Shewhart chart, Precontrol chart and Process Capacity.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.61-73
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• 2016

We consider the wild bootstrap Ljung-Box (LB) test for autocorrelation in residuals of fitted multivariate time series models. The asymptotic chi-square distribution under the IID assumption is traditionally used for the LB test; however, size distortion tends to occur in the usage of the LB test, due to the conditional heteroskedasticity of financial time series. In order to overcome such defects, we propose the wild bootstrap LB test for autocorrelation in residuals of fitted vector autoregressive and error correction models. The simulation study and real data analysis are conducted for finite sample performance.

• Journal of Navigation and Port Research
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• v.27 no.2
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• pp.163-170
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• 2003

This empirical study takes the activation approach for the competitive power of Korean shipping companies in the Korea-China liner routes. Data for this study were collected from Korea/ China/ 3rd flag shipping companies through the 500 questionnaires. The data of 250 respondents were analyzed statistically to verify the hypotheses and to induce Regression Equation which could predicts the influencing level of the determinants to competitive advantage for Korean shipping companies on Korea-China Liner Shipping Routes. Factor Analysis/ Cronbach's Alpha/ Principal Analysis/ Multiple Regression Analysis were used in order to test the hypotheses for the empirical study.