• The Journal of Industrial Distribution & Business
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• v.8 no.4
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• pp.15-21
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• 2017

Purpose - In this work, we examined the causal relationship between credit loans from households (CLH), loan collateralized with housing (LCH) and an interest of certificate of deposit (ICD) among others in South Korea. Furthermore, the optimal forecasts on the underlying model will be obtained and have the potential for applications in the economic field. Research design, data, and methodology - A total of 31 realizations sampled from the 4th quarter in 2008 to the 4th quarter in 2016 was chosen for this research. To achieve the purpose of this study, a regression model with correlated errors was exploited. Furthermore, goodness-of-fit measures was used as tools of optimal model-construction. Results - We found that by applying the regression model with errors component ARMA(1,5) to CLH, the steep and lasting rise can be expected over the next year, with moderate increase of LCH and ICD. Conclusions - Based on 2017-2018 forecasts for CLH, the precipitous and lasting increase can be expected over the next two years, with gradual rise of two major explanatory variables. By affording the assumption that the feedback among variables can exist, we can, in the future, consider more generalized models such as vector autoregressive model and structural equation model, to name a few.

• Journal of the Korea Institute of Building Construction
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• v.17 no.6
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• pp.535-544
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• 2017

This paper analyzes the relations between design errors, prevented by building information modeling (BIM)-based design validation, and their impacts in order to identify critical consideration factors for implementing BIM-based design validation in architecture, engineering, and construction (AEC) projects. More than 800 design errors detected by BIM-based design validation in two BIM-based projects in South Korea are categorized according to their causes (illogical error, discrepancy, and missing item) and work types (structure, architecture, and mechanical, electrical, and plumbing (MEP)). The probabilistic relations among the independent variables, including the causes and work types of design errors, and the dependent variables, including the project delays, cost overruns, low quality, and rework generation that can be caused by these errors, are analyzed using logistic regression. The characteristics of each design error are analyzed by means of face-to-face interviews with practitioners. According to the results, the impacts of design error causes in predicting the probability values of project delays, cost overruns, low quality, and rework generation were statistically meaningful.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.343-350
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• 2022

Purpose: This study evaluated the prevalence of dental implant positioning errors and the most frequently affected oral regions. Materials and Methods: A sample was obtained of CBCT images of 590 dental implants from 230 individuals who underwent diagnosis at a radiology center using cone-beam computed tomography from 2017 to 2020. The following variables were considered: thread exposure, violation of the minimum distance between 2 adjacent implants and between the implant and tooth, and implant contact with anatomical structures. Descriptive data analysis and the Pearson chi-square test(P<0.05) were performed to compare findings according to mouth regions. Results: Most (74.4%) of the 590 implants were poorly positioned, with the posterior region of the maxilla being the region most frequently affected by errors. Among the variables analyzed, the most prevalent was thread exposure (54.7%), followed by implant contact with anatomical structures, violation of the recommended distance between 2 implants and violation of the recommended distance between the implant and teeth. Thread exposure was significantly associated with the anterior region of the mandible (P<0.05). The anterior region of the maxilla was associated with violation of the recommended tooth-implant distance (P<0.05) and the recommended distance between 2 adjacent implants(P<0.05). Implant contact with anatomical structures was significantly more likely to occur in the posterior region of the maxilla (P<0.05). Conclusion: Many implants were poorly positioned in the posterior region of the maxilla. Thread exposure was particularly frequent and was significantly associated with the anterior region of the mandible.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.209-216
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• 2015

Quantile regression models with covariate measurement errors have received a great deal of attention in both the theoretical and the applied statistical literature. A lot of effort has been devoted to develop effective estimation methods for such quantile regression models. In this paper we propose the partially linear support vector orthogonal quantile regression model in the presence of covariate measurement errors. We also provide a generalized approximate cross-validation method for choosing the hyperparameters and the ratios of the error variances which affect the performance of the proposed model. The proposed model is evaluated through simulations.

• KIEAE Journal
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• v.14 no.6
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• pp.87-92
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• 2014

The objectives of this study are to investigate input variables of photovoltaic generation programs and to compare their prediction to actual generation of photovoltaic system in the C city hall and the C city sewage treatment plant. We investigated the actual amount of generation, the forecast amount of generation, the amount of solar radiation data, and calculated the relative errors. We simulated the photovoltaic system of C city hall and the C city sewage treatment plant located in Chungju using existing programs, such as SAM, RETSCREEN, HOMER, PV SYST, Solar Pro. The result of this study are as follows : Through examining the relative errors of monthly predicted and actual generation data, monthly generation data showed big errors in winter season?. Except winter season, actual amount of generation and the predicted amount of generation showed no large errors.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.587-594
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• 2009

In this paper the change point problem of the error terms in linear regression models is considered. Since fixed or stochastic independent variables and weakly dependent errors are assumed, usual multiple regression models and time series models including ARMA are covered. We use the estimates of probability density function based on residuals in order to test the distribution change of the unobserved errors. Under some mild conditions, the test using the residuals is proved to have the same limiting distribution as the test based on true errors.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.163-170
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• 1996

An errors-in-variables model (EVM) differs from the classical regression model in that in the former the independent variable is also subject to error. This paper shows that to assess the applicability of the ordinary least squares (OLS) estimation procedure to the EVM, the relative dispersion of the independent variable to its error variance must be also considered in addition to Mandel's criterion. The effect of physically reducing the variance of errors in the independent variable on the performance of the OLS slope estimator is also discussed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.245-253
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• 1990

In a regression relationship the independent variables are frequently measured with error when measurements are made in the field under less controlled conditions, or when accurate instruments are not available. This paper deals with the prediction problem for the above situation. The integrated mean square error of prediction (IMSE) is developed as a measure of the effect of the errors in the independent variables on the predicted values. The IMSE may be used for assessing the severeness of measurement errors as well as for comparing competing estimators. An example from the area of work measurement is analyzed.

• Journal of the Korean Statistical Society
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• v.13 no.2
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• pp.107-113
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• 1984

In a linear regression model the idependent variables are frequently subject to measurement errors. For this case, the problem of estimating unknown parameters has been extensively discussed in the literature while very few has been concerned with the effect of measurement errors on prediction. This paper investigates the behavior of the predicted values of the dependent variable in terms of the average mean square error of prediction (AMSEP). AMSEP may be used as a criterion for selecting an appropriate estimation method, for designing an estimation experiment, and for developing cost-effective future sampling schemes.

• Korean Journal of Applied Biomechanics
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• v.16 no.4
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• pp.95-103
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• 2006

The purpose of this study was to review the relevant literature about coaching and thereupon, survey the coaching methods used for golf lesson to reinterpret them and thereby, describe in view of kinetics the swing errors committed frequently by amateur golfers and suggest more scientific golf coaching methods. For this purpose, kinetic elements were divided into accuracy and power ones and therewith, the variables affecting such elements were identified. For this study, a total of 60 amateur golfer were sampled, and their swing forms were photographed with two high-speed digital cameras, and the resultant images were analyzed to determine the errors of each form kinetically, which would be analyzed again with the program V1-5000. The kinetic elements could be identified as accuracy, power and accuracy & power. Thus, setup and trajectory were classified into accuracy elements, while differences of inter-joint angles, cocking and delayed hitting. Lastly, timing and axial movement were classified into accuracy & power elements. Three errors were identified in association with setup. The errors related with trajectory elements accounted for most (6) of the 20 errors. Three errors were determined for inter-joint angle differences, and one error was associated with cocking and delayed hitting. Lastly, one error was classified into timing error, while five errors were associated with axial movement. Finally, as a result of arranging the errors into a cross table, it was found that the errors were associated with each other between take-back and back-swing, take-back and follow-through, back-swing and back-swing top, and between back-swing and down-swing. Namely, an error would lead to other error repeatedly. So, it is more effective to identify all the errors for every form and correct them comprehensively rather than single out the errors and correct them one by one.