• International Journal of Human Ecology
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• 제4권2호
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• pp.77-87
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• 2003

This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

• Journal of Positioning, Navigation, and Timing
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• 제2권2호
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• pp.131-137
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• 2013

In this study, positioning results that combined the code observation information of GPS and GLONASS navigation satellites were analyzed. Especially, the distribution of GLONASS satellites observed in Korea and the combined GPS/GLONASS positioning results were presented. The GNSS data received at two reference stations (GRAS in Europe and KOHG in Goheung, Korea) during a day were processed, and the mean value and root mean square (RMS) value of the position error were calculated. The analysis results indicated that the combined GPS/GLONASS positioning did not show significantly improved performance compared to the GPS-only positioning. This could be due to the inter-system hardware bias for GPS/GLONASS receivers, the selection of transformation parameters between reference coordinate systems, the selection of a confidence level for error analysis, or the number of visible satellites at a specific time.

• 응용통계연구
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• 제19권2호
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• pp.271-282
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• 2006

본 논문에서는 범주형과 연속형 변수들이 혼합된 데이터에 적용할 수 있는 나무형 군집화 알고리즘을 제안하였다. 특히 혼합된 변수들이 공통의 의미를 갖도록 하기 위해 범주형 변수들을 전처리하는 방법을 고안하였다. 수치 예로서 SPSS의 신용(credit) 데이터와 독일신용자료(German credit data)에 알고리즘을 적용하고 그 결과를 검토하였다.

• Journal of Forest and Environmental Science
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• 제24권3호
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• pp.137-142
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• 2008

In this paper, we apply a logistic regression model to the data of snow damage on sugi (Cryptomeria japonica) occurred in Toyama prefecture (in Japan) in 2004 for estimating the risk probability. In order to specify the factors effecting snow damage, we apply a model selection procedure determining optimal subset of explanatory variables. In this process we consider the following 3 information criteria, 1) Akaike's information criterion, 2) Baysian information criterion, 3) Bias-corrected Akaike's information criterion. For the selected variables, we give a proper interpretation from the viewpoint of natural disaster.

• Communications for Statistical Applications and Methods
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• 제15권3호
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• pp.333-342
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• 2008

회귀모형에서의 변수선택에 관한 정리를 공분산분석 모형으로 확장하였다. 공분산분석 모형에서 몇개의 회귀변수를 제거한 축소모형을 세우는 경우에 추정량의 변화를 알아본 결과, 회귀계수 뿐만아니라 분산분석계수도 추정량의 편차는 증가하지만 분산은 감소하며, 어떤 경우에는 평균제곱오차도 감소한다는 결론을 얻었다.

• 한국산업융합학회 논문집
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• 제25권6_3호
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• pp.1293-1302
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• 2022

The relationship between homeownership and participation in giving and volunteering overall indicates that homeowners are more likely to give and participate in volunteering organizations than renters. This study compared 'giving and participation in volunteering between homeowners(n=6,078) and renters(3,587) in the 14^th Korean Welfare Panel Survey data collected in 2019. The outcome measure of study is a binary outcome of giving and volunteering participation. This study accounted for a bias arising from selection on observables. Specifically, this study employed a recursive bivariate probit model to simultaneously estimate respondents' participation in giving and volunteering participation and their selection of homeownership. Findings from this study have provided some evidence that homeowners and renters have different behaviors in giving and volunteering participation. Finally, issues relating to homeownership and social outcomes were discussed. Implications for social work practice and research were further discussed.

• 농촌계획
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• 제12권3호
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• pp.81-95
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• 2006

The objective of the this study is to find a way to increase fm household income through investigating their computer applications. We utilized the 2000 Korea Agricultural Survey data and applied a Heckman Selection Model to correct a selection bias. The present study found the following results. First, determinant of income among fm households by the level of computer applications has significant statistical differences based on their choices of computer applications. Accordingly, the application of general linear regression about fm income without adjusting these choices may cause statistical fallacy. Second, it has been reported that increasing the member of household is not directly related to increasing the fm income. In case of computer-own farm household, the effect of decrease in income according to increasing in age was predicted. However, in the fm household not possessing computer, it shows negative relationship. It shows that an agricultural career of farm owner and educational attainment of all farm household members have positive relationship regardless of computer possession. The income of the farm household those main field is not agriculture is also found to be lower than that of farm household whose major earnings come from agriculture.

• 농촌계획
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• 제20권4호
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• pp.193-208
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• 2014

This study aims to identify feasible policy direction of the 6th industrialization in agriculture based on the current agricultural and rural environment in Korea. To do so, this study employes a heckman selection model to correct a probable selection bias, utilizing the Korean agricultural census in 2010 and the agricultural statistics of farm enterprises in 2011. This study focuses on the differences of the farm and off-farm income determinants, according to conjoint types of the 6th industrialization such as Type 1 (primary+secondary+tertiary) vs. Type 2 (primary+secondary or primary+tertiary). The empirical results show Type 2 has much higher possibilities to earn farm and off-farm income in Korea, especially for farm enterprises. This study concludes with providing some policy implications reflecting rural and agricultural environment in Korea.

• 농촌계획
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• 제27권3호
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• pp.47-56
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• 2021

The purpose of this study is to identify the determinants of local farmers' participation and acceptance level in traditional agricultural technology conservation activities, using on the traditional agricultural water utilization system in Uiseong designated as Korea's important agricultural heritage system No. 10. The Heckman sample selection model was used to solve the selection bias. The results show that as the interest in the conservation of the agricultural ecological and environment is high, as the traditional agricultural system in Uiseong is used, as the cultivation area of paddy field increased, and as the age 50s or older, the willingness to participate in conservation activities increased. The results also indicate that as the experience of participating in the conservation of the agricultural ecological and environment and the hours of education are increased, the knowledge of the traditional agricultural system in Uiseong is low, and as the cultivation area of paddy field decreased, the acceptance time for conservation activities increased. The results of this study may contribute to government's policy for traditional agricultural technology conservation.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.