• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.27-41
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• 2008

A graphical method of checking the adequacy of a generalized linear model is proposed. The graph helps to assess the assumption that the link function of mean can be expressed as a linear combination of explanatory variables in the generalized linear model. For the graph the boosting technique is applied to estimate nonparametrically the relationship between the link function of the mean and the explanatory variables, though any other nonparametric regression methods can be applied. Through simulation studies with normal and binary data, the effectiveness of the graph is demonstrated. And we list some limitations and technical details of the graph.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.207-216
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• 2011

Bootstrap is a resampling technique to find an estimate of parameters or to evaluate the estimate. This technique has been used in estimating parameters in linear model(LM) and generalized linear model(GLM). In this paper, we explore the possibility of applying Bootstrapping Residuals, Pairs, and an Estimating Equation that are most widely used in LM and GLM to the generalized estimating equation(GEE) algorithm for modelling repeatedly measured regression data sets. We compared three bootstrapping methods with coefficient and standard error estimates of GEE models from one simulated and one real data set. Overall, the estimates obtained from bootstrap methods are quite comparable, except that estimates from bootstrapping pairs are somewhat different from others. We conjecture that the strange behavior of estimates from bootstrapping pairs comes from the inconsistency of those estimates. However, we need a more thorough simulation study to generalize it since those results are coming from only two small data sets.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.265-275
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• 2009

This paper considers a linear regression model with a spatial autoregressive disturbance with ill-posed data and proposes the generalized maximum entropy(GME) estimator of regression coefficients. The performance of this estimator is investigated via Monte Carlo experiments. The results show that the GME estimator provides efficient and robust estimate for the unknown parameter.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.1-9
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• 2011

Wireless mobile networks that exploit generalized PF scheduling can dynamically allocate network resources by using scheduling parameters. There are limitations to predict throughputs by the conventional stochastic approach in general. Moreover the limitations make it difficult to find appropriate scheduling parameters for achieving the demanded throughputs. This paper derives a prediction algorithm that predicts throughputs of the networks by using deterministic approach. A throughput adjust algorithm and a throughput switching algorithm are derived from the prediction algorithm. The performance of the throughput prediction/switching algorithms is evaluated by a simulator based on IEEE 802.16m system.

• The Mathematical Education
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• v.57 no.1
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• pp.55-74
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• 2018

The purpose of this study is first to examine the relative influence of each error source and to investigate the optimal measurement conditions to ensure satisfactory multiple reliability coefficients based on the teaching aptitude and personality test for pre-service teachers. Participants were 33 students enrolled in mathematics education in a graduate school of education located in the Seoul metropolitan area from 2013 to 2017. The main results were as follows. First, the estimated variance due to residual was highest, followed by nesting of items within domains, graduate students, interactions of graduate students with domains, and domains. Second, total 96 items, with 12 domains containing 8 items in each domain, with cut score of 598, and original 210 items, with 14 domains containing 15 items in each domain, with cut scores of 615 or 716 were optimal measurement conditions to reach acceptable reliability levels based on the joint consideration of dependability coefficients, cut score dependability coefficients, adjusted dependability coefficients, and standard errors of measurement. Third, larger deviations between the arithmetic mean and the cut score indicated higher reliability coefficients of the test results. Finally, this study suggests ways for practitioners to consider how to apply generalizability theory for criterion-referenced tests and how to develop future research based on limitations.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.45-59
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• 2004

GIS가 일반 사용자에게 보급되기 시작하면서 이동 GIS를 활용한 다양한 서비스와 위치 기반서비스들이 등장하고 활용되고 있다. 본 논문에서는 GIS 기반의 위치기반서비스에 대한 일반적인 서비스 프레임워크를 제시하고 서비스가 수행되는 모형을 살펴본다. 또한 이를 통하여 각각의 소요 기술을 파악하고 연구 진행 중인 다양한 기술의 활용방안에 대하여 살펴보도록 한다. 연구내용으로는 먼저 전통적인 GIS를 바탕으로 하는 GIS 기반의 위치기반서비스 구조를 발굴하여 일반적인 서비스 프레임워크로 작성한다. 서비스 프레임워크에서는 전통 GIS와 위치기반서비스의 서비스 수행관계, 인터페이스 관계 등을 표현하여 일반화하도록 하고, 이를 기반으로 한 서비스 운영형태를 제시한다. 그리고 서비스 프레임워크에 포함된 관련 분야의 기술 분류를 수행한다. 기술 분류는 위치기반서비스와 GIS를 바탕으로 주요 요구기술을 도출하여 이를 기능별로 구분하여 표준화 기술을 분류한다. 이들 기술은 각각의 기술발전 과정에 따라 다양한 과정으로 발전하게 되고 이에 따라서 서비스의 모양도 다양한 형태로 발전할 것으로 보인다. 마지막으로 이를 종합한 기술 로드맵을 제시하여 표준화 및 향후 발전방안을 제시하게 된다. 이를 바탕으로 GIS에 기반한 위치기반서비스의 일반화된 서비스 모형을 제시할 수 있고, 필요한 기술의 발굴, 기술발전에 따른 다양한 서비스의 예측이 가능할 것으로 보이며 GIS 서비스의 일반화에 크게 기여할 것으로 보인다.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.208-217
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• 2014

This paper propose an adaptive control of symmetry contribution based generalized symmetry transform. which can be controlled symmetry contribution according to the intensity orientation of two pixels. In the proposed method, we define the C-D(convergent and divergent)plane which represents convergence and divergence region of gradient pairs. and used the gaussian phase wight function, with respect to the distance from the gradient pair to an extreme point, in calculating the symmetry contribution. The proposed method can be detect the object more efficiently by adaptive controlling the cut-off frequency of the gaussian phase wight function. To evaluate a performance of the proposed method, we compare the proposed method and conventional GST method in various images including IR image. we prove that the proposed method have better performance in object detection.

• Journal of Korean Society of Transportation
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• v.11 no.1
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• pp.55-66
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• 1993

본 논문에서는 최근에 소개된 일반화중력모형(Generalized Gravity Model)파라메터의 최우추정치(Maximum Likelihood Estimates) 계산을 위한 새로운 알고리즘을 이론적으로 도출하였다. 개발된 알고리즘은 첫째 계산속도, 둘째 정밀도, 셋째 모형변수(예컨데 통행시간, 통행비용 등)들 간에 공선성(multicolinearity)이 존재할 경우의 계산능력, 넷째 대규모 스케일의 기.종점자료(large O-D Matrices)에 적용시의 계산능력, 다섯째 모형변수의 개수에 따른 계산능력의 평가기준에서 그 계산실적이 기존의 알고리즘과 비교 평가 되었다. 제안된 기법중에서 Modified Scoring 기법은 계산속도 및 정밀도등 앞서 나열한 계산능력의 평가기준 중 모든 부문에서 매우 탁월한 계산실적을 보이는 것으로 판명되었다. 따라서 최선의 추정치를 보장하는 최우추정기법이 대규모 스케일의 교통계획 적용에도 큰 비용(시간)부담없이 손쉽게 적용될 수 있게 되었다. 제안된 새로운 알고리즘의 적용시 교통계획분야에 가져올 수 있는 기대효과는 다음과 같다. 첫째, 최우추정법이 대규모 O-D 통행표에 쉽게 적용될 수 있고 또한 PC등 소형 컴퓨터에서도 처리가 쉽다. 둘째, 모형설명변수의 자유로운 선택등 통계적실험(experimentation)을 가능케 한다. 셋째, 중력모형이 내재되어 있는 결합모형(Combined Model)의 정산속도를 높인다. 넷째, IVHS(Intelligent Vehicle and Highway System)와 같은 분야에서 온라인(On-line)모형정산을 가능케 할 수 있다.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.561-575
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• 2014

In this paper, we propose a penalized likelihood method to detect local spatial clusters associated with disease. The key computational algorithm is based on genlasso by Tibshirani and Taylor (2011). The proposed method has two main advantages over Kulldorff's method which is popoular to detect local spatial clusters. First, it is not needed to specify a proper cluster size a priori. Second, any type of covariate can be incorporated and, it is possible to find local spatial clusters adjusted for some demographic variables. We illustrate our proposed method using tuberculosis data from Seoul.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.665-671
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• 2010

This paper propose the DDEGST(divergent-direction-emphasis generalized symmetry transform) which emphasis the symmetry of divergent intensity orientation for effective target extraction in FLIR(forward looking infra-red) images. In the proposed method, we use the exponential function instead of cosine function as a phase weight function in the generalized symmetry transform for effective target extraction in FLIR images which contain a target with higher intensity than a background intensity. To evaluate the performance of the proposed method, we compare the proposed mehtod with conventional GST method in experiments. We prove that the proposed method have better performance in IR images.