• 응용통계연구
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• 제34권6호
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• pp.937-944
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• 2021

본 연구는 부분선형모형에서 변수선택의 문제를 다룬다. 부분선형모형은 평활화모수 추정과 같은 비모수 추정과 선형설명변수에 대한 추정의 문제를 함께 포함하고 있어 변수선택이 쉽지 않다. 본 연구에서는 빠른 전진선택법인 LARS 를 이용한 변수선택법을 제시한다. 제안된 방법은 LARS에 의하여 선별된 변수들에 대하여 t-검정, 가능한 모든 회귀모형 비교 또는 단계별 선택법을 적용한다. 제안된 방법들의 효율성을 비교하기 위하여 실제데이터에 적용한 예제와 모의실험 결과가 제시된다.

• Journal of applied mathematics & informatics
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• 제8권2호
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• pp.641-649
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• 2001

A procedure of detecting change-points is considered with split linear fitting idea from Hall and Titterington(1992). At each given point, left, central and right linear fits are compared to detect the discontinuities or change-points. A simulation study is done with various types of change models and shows that the suggested technique can be a flexible data-analytic tool.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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• pp.171-179
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• 2006

For the problem of variable selection in linear models, we consider the errors are correlated with V covariance matrix. Hocking's theorems on the effects of the overfitting and the underfitting in linear model are extended to the less than full rank and correlated error model, and to the ANCOVA model.

• Structural Engineering and Mechanics
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• 제26권1호
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• pp.15-30
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• 2007

In the paper, one focuses on the problem of duality in non-linear programming, applied to the solution of no-tension problems by means of Limit Analysis (LA) theorems for Not Resisting Tension (NRT) models. In details, one demonstrates that, starting from the application of the duality theory to the non-linear program defined by the static theorem approach for a discrete NRT model, this procedure results in the definition of a dual problem that has a significant physical meaning: the formulation of the kinematic theorem.

• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.303-309
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• 1995

Many measures to detect multicollinearity in linear regression have been proposed in statistics and numerical analysis literature. Among them, condition number and variance inflation factor(VIF) are most popular. In this study, we give new interpretations of condition number and VIF in linear regression, using geometry on the explanatory space. In the same line, we derive natural measures of condition number and VIF for logistic regression. These computer intensive measures can be easily extended to evaluate multicollinearity in generalized linear models.

• Imaging Science in Dentistry
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• 제51권4호
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• pp.429-438
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• 2021

Purpose: This study investigated the accuracy of laser-scanned models and 3-dimensional(3D) rendered cone-beam computed tomography (CBCT) compared to the gold standard (plaster casts) for linear measurements on dental arches. Materials and Methods: CBCT scans and plaster models from 30 patients were retrieved. Plaster models were scanned by an Emerald laser scanner (Planmeca, Helsinki, Finland). Sixteen different measurements, encompassing the mesiodistal width of teeth and both arches' length and width, were calculated using various landmarks. Linear measurements were made on laser-scanned models using Autodesk Meshmixer software v. 3.0 (Autodesk, Mill Valley, CA, USA), on 3D-rendered CBCT models using OnDemand 3D v. 1.0 (Cybermed, Seoul, Korea) and on plaster casts by a digital caliper. Descriptive statistics, the paired t-test, and intra- and inter-class correlation coefficients were used to analyze the data. Results: There were statistically significant differences between some measurements on plaster casts and laser-scanned or 3D-rendered CBCT models (P<0.05). Molar mesiodistal width and mandibular anterior arch width deviated significantly different from the gold standard in both methods. The largest mean differences of laser-scanned and 3D-rendered CBCT models compared to the gold standard were 0.12±0.23 mm and 0.42±0.53 mm, respectively. Most of the mean differences were not clinically significant. The intra- and inter-class correlation results were acceptable for all measurements(>0.830) and between observers(>0.801). Conclusion: The 3D-rendered CBCT images and laser-scanned models were useful and accurate alternatives to conventional plaster models. They could be used for clinical purposes in orthodontics and prostheses.

• 한국보건간호학회지
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• 제31권1호
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• pp.5-18
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• 2017

Purpose: This study was conducted to suggest a method for financial projection of health insurance expenditures that reflects future changes in demographic structure. Methods: Using data associated with the number of patients and health insurance cost per patient, generalized linear models (GLM) were fitted with demographic explanatory variables. Models were constructed separately for individual medical departments, types of medical service, and types of public health insurance. Goodness-of-fit of most of the applied GLM models was quite satisfactory. By combining estimates of frequency and severity from the constructed models and results of the population projection, total annual health insurance expenditures were projected through year 2060. Results: Expenditures for medical departments associated with diseases that are more frequent in elderly peoples are expected to increase steeply, leading to considerable increases in overall health insurance expenditures. The suggested method can contribute to improvement of the accuracy of financial projection. Conclusion: The overall demands for medical service, medical personnel, and relevant facilities in the future are expected to increase as the proportion of elderly people increases. Application of a more reasonable estimation method reflecting changes in demographic structure will help develop health policies relevant to above mentioned resources.

• 대한원격탐사학회지
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• 제28권6호
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• pp.597-609
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• 2012

Leaf area index (LAI) is important in explaining the ability of the crop to intercept solar energy for biomass production and in understanding the impact of crop management practices. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal series of IKONOS, Landsat TM, and MODIS satellite images using empirical models and demonstrates its use with data collected at Missouri field sites. LAI data were obtained several times during the 2002 growing season at monitoring sites established in two central Missouri experimental fields, one planted to soybean (Glycine max L.) and the other planted to corn (Zea mays L.). Satellite images at varying spatial and spectral resolutions were acquired and the data were extracted to calculate normalized difference vegetation index (NDVI) after geometric and atmospheric correction. Linear, exponential, and expolinear models were developed to relate temporal NDVI to measured LAI data. Models using IKONOS NDVI estimated LAI of both soybean and corn better than those using Landsat TM or MODIS NDVI. Expolinear models provided more accurate results than linear or exponential models.

• 한국농공학회논문집
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• 제62권1호
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• pp.61-70
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• 2020

To estimate the ventilation volume of mechanically ventilated swine farms, various regression models were applied, and errors were compared to select the regression model that can best simulate actual data. Linear regression, linear spline, polynomial regression (degrees 2 and 3), logistic curve, generalized additive model (GAM), and gompertz curve were compared. Overfitting models were excluded even when the error rate was small. The evaluation criteria were root mean square error (RMSE) and mean absolute percentage error (MAPE). The evaluation results indicated that degree 3 exhibited the lowest error rate; however, an overestimation contradiction was observed in a certain section. The logistic curve was the most stable and superior to all the models. In the estimation of ventilation volume by all of the models, the estimated ventilation volume of the logistic curve was the smallest except for the model with a large error rate and the overestimated model.

• KEPCO Journal on Electric Power and Energy
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• 제5권3호
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• pp.201-207
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• 2019

An anchorage system is essential for most reinforced concrete structures to connect building components. Therefore, the prediction of strength of the anchor is very important issue for safety of the structures themselves as well as structural components. The prediction models in existing design codes are, however, not applicable for large anchors because they are based on the small size anchors with diameters under 50 mm. In this paper, new prediction models for strength of a single anchor, especially the tensile strength of a single anchor, is developed from the experimental results with consideration of size effect. Size effect in the existing models such as ACI or CCD method is based on the linear fracture mechanics which is very conservative way to consider the size effect. Therefore, new models are developed based on the nonlinear fracture mechanics rather than the linear fracture mechanics for more reasonable prediction. New models are proposed by the regression analysis of the experimental results and it can predict the tensile strength of both small and large anchors.