• Title/Summary/Keyword: 로지스틱 회귀 모형

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Assessing the accuracy of the maximum likelihood estimator in logistic regression models (로지스틱 회귀모형에서 최우추정량의 정확도 산정)

  • 이기원;손건태;정윤식
    • The Korean Journal of Applied Statistics
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    • v.6 no.2
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    • pp.393-399
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    • 1993
  • When we compute the maximum likelihood estimators of the parameters for the logistic regression models, which are useful in studying the relationship between the binary response variable and the explanatory variable, the standard error calculations are usually based on the second derivative of log-likelihood function. On the other hand, an estimator of the Fisher information motivated from the fact that the expectation of the cross-product of the first derivative of the log-likelihood function gives the Fisher information is expected to have similar asymptotic properties. These estimators of Fisher information are closely related with the iterative algorithm to get the maximum likelihood estimator. The average numbers of iterations to achieve the maximum likelihood estimator are compared to find out which method is more efficient, and the estimators of the variance from each method are compared as estimators of the asymptotic variance.

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Undecided inference using the difference of AUCs (AUC 차이를 이용한 미결정자 추론방법)

  • Hong, Chong Sun;Na, Hae Rin
    • The Korean Journal of Applied Statistics
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    • v.34 no.2
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    • pp.141-152
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    • 2021
  • A new statistical model needs additional variables in order to re-evaluate the undecided inference. Then the MNAR assumption is required, since the probabilities for the positivity of the indeterminant and the determinant is calculated differently. In this study, since two statistical models have a hierarchical relationship, we determine the undecided inference under the MNAR assumption using the confidence interval of the difference between two AUCs. Among many methods of estimating the confidence interval of the AUC difference, it is found that four kinds of methods show excellent performance through simulations. And based on these methods, we propose a variable selection method that are useful for the undecided inference using logistic regression models.

Estimation of Freeway Accident Likelihood using Real-time Traffic Data (실시간 교통자료 기반 고속도로 교통사고 발생 가능성 추정 모형)

  • Park, Joon-Hyung;Oh, Cheol;NamKoong, Seong
    • Journal of Korean Society of Transportation
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    • v.26 no.2
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    • pp.157-166
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    • 2008
  • This study proposed a model to estimate traffic accident likelihood using real-time traffic data obtained from freeway traffic surveillance systems. Traffic variables representing spatio-temporal variations of traffic conditions were utilized as independent variables in the proposed models. Binary logistics regression modelings were conducted to correlate traffic variables and accident data that were collected from the Seohaean freeway during recent three years, from 2004 to 2006. To apply more reliable traffic variables, outlier filtering and data imputation were also performed. The outcomes of the model that are actually probabilistic measures of accident occurrence would be effectively utilized not only in designing warning information systems but also in evaluating the effectiveness of various traffic operations strategies in terms of traffic safety.

The Effect of Overdesign on Titan Rocket Engine Reliability and Development Cost (과설계가 타이탄 로켓엔진의 신뢰도 및 개발비용에 미치는 영향)

  • Kim, Kyungmee O.;Hwang, Junwoo
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.43 no.4
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    • pp.334-340
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    • 2015
  • Engine derating is often considered for reliability benefits because lower power operation reduces its failure probability. To be derated during operation, however, the engine must be initially overdesigned. The engine overdesign is cost effective only if reliability increased from derating is enough to offset the initial increase in the development cost caused from the overdesign. The purpose of this paper is to provide an analytical model to consider a trade-off between the engine overdesign and derating. We use a logistic regression model to explain reliability growth in the number of hot firing tests for a fixed power level. Using the Transcost model with the reliability growth model, we show that 10% overdesign of Titan rocket engine decreases its development cost by about 9% and 23% depending on the reliability requirement. We also point out that such a cost reduction depends on the fuel type a rocket uses.

Credit Scoring Using Splines (스플라인을 이용한 신용 평점화)

  • Koo Ja-Yong;Choi Daewoo;Choi Min-Sung
    • The Korean Journal of Applied Statistics
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    • v.18 no.3
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    • pp.543-553
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    • 2005
  • Linear logistic regression is one of the most widely used method for credit scoring in credit risk management. This paper deals with credit scoring using splines based on Logistic regression. Linear splines and an automatic basis selection algorithm are adopted. The final model is an example of the generalized additive model. A simulation using a real data set is used to illustrate the performance of the spline method.

Study of child abuse families using logistic regression models (로지스틱회귀모형을 활용한 아동학대 가족의 연구)

  • Min, Dae Kee;Choi, Mi Kyung
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1327-1336
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    • 2016
  • Most cases of child abuse in South Korea are caused by parents in the family home. Currently, these types of incidents are growing. Child abuse creates irreparable damage to a child's development and its effects are prolonged. This damage can create a maladjusted adolescent and adult criminal acts. Because of this damage and the long lasting effects on a person and society as a whole, special attention needs to be paid to this pressing issue. South Korea's rapidly changing social environment has created a variety of new family forms including dual-income families and single-parent families. With the current economic downturn and accompanying employment instability, many families exist in uneasy financial and emotional states. The children in these stressful family environments are the most vulnerable and live in risk of experiencing physical or psychological abuse from their parents. In the context of significant and often difficult social changes, this study identifies the characteristics of child abuse based on family status and parental mental health.

IRT 모수 추정에서 초기값에 관한 연구

  • Park, Yeong-Seon;Cha, Gyeong-Jun;Jang, Chang-Won
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.05a
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    • pp.7-12
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    • 2003
  • 문항반응이론(IRT)에서 문항특성곡선(ICC)의 모수를 추정하는 경우에 발생되는 초기값(initial value) 문제를 비선형 로지스틱모형을 선형 회귀모형으로 근사화하여 해결하고자 하였다. 특히, 신규 또는 잡음이 섞인(local fluctuation) 문항의 직접적인 평가와 소규모집단별 검사가 이루어질 수 있는 현실적 문제에서 모수추정의 대안으로서 그 의의가 있을 수 있다.

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Analysis-based Pedestrian Traffic Incident Analysis Based on Logistic Regression (로지스틱 회귀분석 기반 노인 보행자 교통사고 요인 분석)

  • Siwon Kim;Jeongwon Gil;Jaekyung Kwon;Jae seong Hwang;Choul ki Lee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.2
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    • pp.15-31
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    • 2024
  • The characteristics of elderly traffic accidents were identified by reflecting the situation of the elderly population in Korea, which is entering an ultra-aging society, and the relationship between independent and dependent variables was analyzed by classifying traffic accidents of serious or higher and traffic accidents of minor or lower in elderly pedestrian traffic accidents using binomial variables. Data collection, processing, and variable selection were performed by acquiring data from the elderly pedestrian traffic accident analysis system (TAAS) for the past 10 years (from 13 to 22 years), and basic statistics and analysis by accident factors were performed. A total of 15 influencing variables were derived by applying the logistic regression model, and the influencing variables that have the greatest influence on the probability of a traffic accident involving severe or higher elderly pedestrians were derived. After that, statistical tests were performed to analyze the suitability of the logistic model, and a method for predicting the probability of a traffic accident according to the construction of a prediction model was presented.

Analysis of Influential Factors of Roadkill Occurrence - A Case Study of Seorak National Park - (로드킬 발생 영향요인 분석 - 설악산 국립공원 44번 국도를 대상으로 -)

  • Son, Seung-Woo;Kil, Sung-Ho;Yun, Young-Jo;Yoon, Jeong-Ho;Jeon, Hyung-Jin;Son, Young-Hoon;Kim, Min-Sun
    • Journal of the Korean Institute of Landscape Architecture
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    • v.44 no.3
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    • pp.1-12
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    • 2016
  • This study aimed to interpret the fundamental cause of road-kill occurrences and analyzed spatial characteristics of the road-kill locations from Route 44 in Seorak National Park, Korea. Logistic regression analysis was utilized for backward elimination on variables. Seorak National Park Service has constructed GIS-data of 81 road-kill occurrences from 2008 to 2013 and these data were assigned as dependent variables in this study. Considered as independent variables from previous studies and field surveys, vegetation age-class, distance to streams, coverage of fences and retaining walls, and distance to building sites were assigned as road-kill impact factors. The coverage of fences and retaining walls(-1.0135) was shown as the most influential factor whereas vegetation age-class(0.0001) was the least influential among all of the significant factor estimates. Accordingly, the rate of road-kill occurrence can increase as the distance to building sites and stream becomes closer and vegetation age-class becomes higher. The predictive accuracy of road-kill occurrence was shown to be 72.2% as a result of analysis, assuming as partial causes of road-kill occurrences reflecting spatial characteristics. This study can be regarded as beneficial to provide objective basis for spatial decision making including road-kill occurrence mitigation policies and plans in the future.

Development of the U-turn Accident Model at Signalized Intersections in Urban Areas by Logistic Regression Analysis (로지스틱 회귀분석에 의한 도시부 신호교차로 유턴 사고모형 개발)

  • Kang, Jong Ho;Kim, Kyung Whan;Kim, Seong Mun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.4
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    • pp.1279-1287
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    • 2014
  • The purpose of this study is to develop the U-turn accident model at signalized intersections in urban areas. The characteristics of the accidents which are associated with U-turn operation at 3 and 4-legged signalized intersections was analyzed and the U-turn accident model was developed by regression analysis in Changwon city. First, in order to analyze the effectiveness on traffic accidents by U-turn installation, the difference of mean of traffic accident number are measured between two groups which are composed by whether or not U-turn installation the groups by Mann-Whitney U test. The result of significance test showed that intergroup comparison on mean by accident types made difference except rear-end accident type and by accident locations exit section only showed difference in significance level at 4-legged intersections, so the accident number have more where the U-turn is permitted than not. Response measures about the number of accidents were classified by whether accidents occurred and accident model were constructed using binomial logistic regression analysis method. The developed models show that the variables of conflict traffic, number of opposing lane are adopted as independent variable for both intersections. The variables of longitudinal grade for 3-legged signalized intersection and number of crosswalk for 4-legged signalized intersection at which the U-turn is permitted is adopted as independent variable only. These study results suggest that U-turn would be permitted at the intersection where the number of opposing lane is more than 3.5 each, the longitudinal grade of opposing road is upward flow and there is need to establish the U-turn traffic sign at signalized intersections.