• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1153-1165
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• 2017

Structural equation modeling (SEM) is a basic tool for testing theories in a variety of disciplines. A maximum likelihood (ML) method for parameter estimation is by far the most widely used in SEM. Alternatively, two-stage least squares (2SLS) estimator has been proposed as a more robust procedure to address model misspecification. A regularized extension of 2SLS, two-stage ridge least squares (2SRLS) has recently been introduced as an alternative to ML to effectively handle the small-sample-size issue. However, it is unclear whether and when misspecification and small sample sizes may pose problems in theory testing with 2SLS, 2SRLS, and ML. The purpose of this article is to evaluate the three estimation methods in terms of inferences errors as well as parameter recovery under two experimental conditions. We find that: 1) when the model is misspecified, 2SRLS tends to recover parameters better than the other two estimation methods; 2) Regardless of specification errors, 2SRLS produces small or relatively acceptable Type II error rates for the small sample sizes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1B
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• pp.9-20
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• 2012

Recently to overcome limitations of conceptual, hydrological and physics based models for flood stage forecasting, multiple linear regression model as one of data-driven models have been widely adopted for forecasting flood streamflow(stage). The objectives of this study are to compare performance of different multiple linear regression models according to regression coefficient estimation methods and determine most effective multiple linear regression flood stage forecasting models. To do this, the time scale was determined through the autocorrelation analysis of input data and different flood stage forecasting models developed using regression coefficient estimation methods such as LS(least square), WLS(weighted least square), SPW(stepwise) was applied to flood events in Jungrang stream. To evaluate performance of established models, fours statistical indices were used, namely; Root mean square error(RMSE), Nash Sutcliffe efficiency coefficient (NSEC), mean absolute error (MAE), adjusted coefficient of determination($R^{*2}$). The results show that the flood stage forecasting model using SPW(stepwise) parameter estimation can carry out the river flood stage prediction better in comparison with others, and the flood stage forecasting model using LS(least square) parameter estimation is also found to be slightly better than the flood stage forecasting model using WLS(weighted least square) parameter estimation.

• Geophysics and Geophysical Exploration
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• v.10 no.2
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• pp.147-153
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• 2007

The conjugate gradient (CG) method is one of the most efficient algorithms for solving a linear system of equations. In addition to being used as a linear equation solver, it can be applied to a least-squares problem. When the CG method is applied to large-scale three-dimensional inversion of magnetotelluric data, two approaches have been pursued; one is the linear CG inversion in which each step of the Gauss-Newton iteration is incompletely solved using a truncated CG technique, and the other is referred to as the nonlinear CG inversion in which CG is directly applied to the minimization of objective functional for a nonlinear inverse problem. In each procedure we only need to compute the effect of the sensitivity matrix or its transpose multiplying an arbitrary vector, significantly reducing the computational requirements needed to do large-scale inversion.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.269-277
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• 2006

We propose a new expert system for recovering the broken fragments of relics into an original form using computer graphics and image processing. This paper presents a system with an application to tombstones objects of flat plane with letters carved in for assembling the fragments by placing their respective fragments in the right position. The matching process contains three sub-processes: aligning the front and letters of an object, identifying the matching directions, and determining the detailed matching positions. We apply least squares fitting, vector inner product, and geometric and RGB errors to the matching process. It turned out that 2-D translations via fragments-alignment enable us to save the computational load significantly. Based on experimental results from the damaged cultural fragments, the performance of the proposed method is illustrated.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.510-518
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• 2018

Purpose: The objective of this research is to analyze the effects of industrial complex sites to manufacturing business of South Korea. Method: This research first investigates previous relative studies for employment factors of industrial complex sites. Second, this research identifies employment decision factors of industrial complex sites by applying the two-stage ordinary least squares method to the Korea Industrial Complex Directory and the census data on establishments published by the Statistics Korea. Third, this research provides findings and policy recommendations based on study results. Results: The number of major companies, production quantity, and diversity of manufacturing have positive impacts to employment of industrial complex. The ratio of foreign workers, the number of universities and colleges, and the fiscal self-reliance ratio are also important to employment of industrial complex. Conclusion: The employment enhancement policy of industrial complex should consider regional characteristics as well as infrastructure of industrial complex.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.395-400
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• 1997

An important quality characteristic of a software reliability.Software reliablilty growh models prvied the tools to evluate and moniter the reliabolty growth behavior of the sofwate during the testing phase Therefore failure data collected during the testing phase should be continmuosly analyzed on the basis of some selected software reliability growth models.For the cases where nonhomogeneous Poisson proxess models are the candiate models,we suggest Poisson regression model, which expresses the relationship between the expeted and actual failures counts in disjonint time intervals,for analyzing the failure count data.The weighted lest squares method is then used to-estimate the paramethers in the parameters in the model:The resulting estimators are equivalent to the maximum likelihood estimators. The method is illustrated by analyzing the failutr count data gathered from a large- scale switchong system.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.76-78
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• 2006

현재 심혈관 질환은 암 다음으로 높은 사망 원인으로 기록되고 있어 심혈관 질환에 대한 초기 진단은 질환의 치료에 매우 중요한 문제로 대두되고 있다. 본 논문에서는 SVM을 이용하여 심혈관질환 환자의 질환 단계를 예측하였다. 일반적으로 이진분류에 사용되는 SVM을 이용하여 정상 및 질환 $1{\sim}3$기의 총 4가지 분류가 필요한 다분류 분류문제를 처리하기 위해서 논문에서는 독립적 학습된 단일 SVM 분류기들을 결합하여 분류를 수행하는 SVM 앙상블 방법을 사용하였다. 단일 분류기의 결합은 Majority voting, 최소자승에러기반 가중치 부여, 2단계층 결합 등의 방법으로 수행하여 심혈관 질환 분류에 적합한 앙상블의 구성을 시도하였다. 실험 데이터는 (주)제노프라의 압타머 칩 데이터를 사용하였다. 서로 다른 데이터를 이용하여 학습된 이종의 SVM들을 결합한 결과 질환단계 예측에 있어서 단일 SVM을 이용하여 질환 단계를 예측하는 경우 보다 향상된 질환단계 예측 성능을 관찰할 수 있었으며, 심혈관 질환의 예측에 대해서는 단일 SVM 분류기의 2단 계층 결합법이 가장 좋은 성능을 보임을 확인하였다.

• Korean Journal of Food Science and Technology
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• v.25 no.2
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• pp.178-184
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• 1993

The procedure using equivalent time at reference temperature has been assessed for the estimation of kinetic parameters with experimental data. Kinetic studies of nonenzymatic browning reaction in model and food system were carried out with linearly increasing temperature method. These kinetic parameters, n, $k_{ref}$ and $E_a$ of the systems were evaluated from original data in one step by nonlinear least square regression. The one step procedure yielded efficiently accurate parameter estimation. Computer simulated data with the kinetic models were well consistent with experimental data (average correlation coefficient=0.96).

• The Korean Journal of Financial Management
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• v.18 no.2
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• pp.57-79
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• 2001

본 연구에서는 우리나라 234개 상장기업을 대상으로 기업의 소유구조와 자본구조의 상호관계가 기업다각화에 미치는 영향을 2단계 최소자승법(2SLS)을 이용하여 분석하였다. 우리나라 기업의 소유구조와 자본구조의 상호관계를 분석한 결과를 요약하면 첫째, 1996년부터 1999년까지의 전기간 분석에서 우리나라 기업은 소유구조와 자본구조 정책을 서로 연계하여 결정하는 것으로 나타났다. 그러나 IMF 경제위기 전후기간으로 구분하여 상호영향관계를 분석한 결과에 의하면 IMF 이전기간에는 소유구조와 자본구조가 상호의존적인 영향관계가 있는 것으로 나타났지만, IMF 이후기간에는 소유구조와 자본구조의 상호영향관계를 발견할 수 없었다. 둘째, 내부자는 부채사용에 따른 재무위험의 부담을 줄이기 위해 레버리지 비율이 높으면 내부지분율을 감소시키는 것으로 나타났다. 넷째, 내부지분율이 높으면 내부자는 자신이 부담해야 하는 재무위험을 줄이기 위해 레버리지 비율을 낮추는 것으로 분석되었다. 한편, 소유구조와 자본구조의 상호관계가 기업다각화에 미치는 영향을 분석한 결과에 의하면, 소유구조와 자본구조의 상호관계가 기업다각화 수준에 영향을 미치지 않는 것으로 나타났다.

• Environmental and Resource Economics Review
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• v.6 no.2
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• pp.259-274
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• 1997

본 논문은 쓰레기종량제 하에서 가격유인책 및 다른 사회 경제적 변수가 가정의 쓰레기발생과 재활용품배출에 미치는 효과를 분석하고 있다. 개별 가정설문자료를 이용하여 가정의 쓰레기발생과 재활용품배출에 대한 구조적 방정식을 3단계 최소자승법으로 추정하였다. 추정결과 가계소득과 가족 수는 쓰레기발생량에 정의 관계로 영향을 미치며, 재활용품배출량은 가정주부의 시간가치와는 역의 관계를 가지고 교육수준과는 정의 관계를 보이고 있다. 쓰레기봉투가격의 인상은 쓰레기발생량에는 영향을 주지 않고 재활용품배출량의 증가를 통해 쓰레기수거서비스에 대한 수요를 감소시키는 것으로 나타난다. 가정에서 분리수거를 통해 재활용할 수 있는 잠재적 재활용가능량은 정부의 재활용품목의 지정 및 재활용기술에 의해 제한되기 때문에 쓰레기가격의 대폭적 인상을 통해 쓰레기수거서비스의 감소를 유도하는 것은 한계가 있는 것으로 보인다.