• 제목/요약/키워드: Binomial Logistic Model

검색결과 38건 처리시간 0.03초

Logistic regression model for major separation rate

  • 최재성
    • Journal of the Korean Data and Information Science Society
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    • 제13권2호
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    • pp.129-138
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    • 2002
  • This paper deals with logistic regression models for analysing separation rates from majors. The model building procedure shows how to incoporate the effects of some factors causing from three-way nested sampling scheme and discusses what type of characteristics as independent variables directly affecting the rates should be considered.

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계층 이항 로지스틱모형에 의한 고속도로 교통사고 심각도 분석 (Analysis of Traffic Crash Severity on Freeway Using Hierarchical Binomial Logistic Model)

  • 문승라;이영인
    • 한국도로학회논문집
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    • 제13권4호
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    • pp.199-209
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    • 2011
  • 교통사고발생시 사고 심각도에 영향을 미치는 요인과 그 관계를 이해하는 것은 기하구조나 환경 측면에서 교통사고 발생을 예방하고 운전자와 사고 차량의 특성을 이해하는데 도움을 준다. 본 연구에서는 계층 이항 로지스틱모형에 의해 고속도로 교통사고 심각도에 영향을 미치는 요인을 파악하고 영향변수 간 차이를 나타내는 비교위험도(odds ratio)를 도출하였다. 사고 심각도는 인명피해와 차량피해로 구분하여 사망사고모형과 차량완파사고모형을 구축하였다, 종속변수는 사망자 발생과 완파차량 발생 여부이며, 각각 사고-탑승자, 사고-차량의 2수준 계층구조를 적용하였다. 추정 결과 설명변수의 고정효과는 두 모형이 유사한 결과를 보이나 종속변수의 속성에 따라 차별화된 결과를 나타내기도 하였다. 본선과 진출입부에서의 사고가 가장 위험하며, 중앙선 침범과 통행위반, 과속 사고의 상해나 차량 파손 위험도가 높고, 충돌사고와 추돌사고, 화재 사고의 피해가 크다. 사고 심각도는 노면 상태나 시야 조건 등 외부환경에 영향을 받으나 기하구조 조건은 관련이 없다.

로지스틱 회귀모형과 머신러닝 모형을 활용한 주요산업의 부산 지역총생산 및 고용 효과 예측 (Prediction on Busan's Gross Product and Employment of Major Industry with Logistic Regression and Machine Learning Model)

  • 이재득
    • 무역학회지
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    • 제47권2호
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    • pp.69-88
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    • 2022
  • This paper aims to predict Busan's regional product and employment using the logistic regression models and machine learning models. The following are the main findings of the empirical analysis. First, the OLS regression model shows that the main industries such as electricity and electronics, machine and transport, and finance and insurance affect the Busan's income positively. Second, the binomial logistic regression models show that the Busan's strategic industries such as the future transport machinery, life-care, and smart marine industries contribute on the Busan's income in large order. Third, the multinomial logistic regression models show that the Korea's main industries such as the precise machinery, transport equipment, and machinery influence the Busan's economy positively. And Korea's exports and the depreciation can affect Busan's economy more positively at the higher employment level. Fourth, the voting ensemble model show the higher predictive power than artificial neural network model and support vector machine models. Furthermore, the gradient boosting model and the random forest show the higher predictive power than the voting model in large order.

폴랴-감마 잠재변수에 기반한 베이지안 영과잉 음이항 회귀모형: 약학 자료에의 응용 (A Bayesian zero-inflated negative binomial regression model based on Pólya-Gamma latent variables with an application to pharmaceutical data)

  • 서기태;황범석
    • 응용통계연구
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    • 제35권2호
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    • pp.311-325
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    • 2022
  • 0의 값을 과도하게 포함하는 가산자료는 다양한 연구 분야에서 흔히 나타난다. 영과잉 모형은 영과잉 가산자료를 분석하기 위해 가장 일반적으로 사용되는 모형이다. 영과잉 모형에 대한 전통적인 베이지안 추론은 조건부 사후분포의 형태가 폐쇄형 분포로 나타나지 않아 모형 적합 과정이 용이하지 않다는 한계점이 존재했다. 그러나 최근 Pillow와 Scott (2012)과 Polson 등 (2013)이 제안한 폴랴-감마 자료확대전략으로 인해, 로지스틱 회귀모형과 음이항 회귀모형에서 깁스 샘플링을 통한 추론이 가능해지면서, 영과잉 모형에 대한 베이지안 추론이 용이해졌다. 본 논문에서는 베이지안 추론에 기반한 영과잉 음이항 회귀모형을 Min과 Agresti(2005)에서 분석된 약학 연구 자료에 적용해본다. 분석에 사용된 자료는 경시적 영과잉 가산자료로 복잡한 자료 구조를 가지고 있다. 모형 적합 과정에서는 깁스 샘플링을 통한 추론을 수행하기 위해 폴랴-감마 자료확대전략을 사용한다.

저농약인증 농가의 유기.무농약 전환의향 분석 (Research on Farming Practice Change of Low-pesticide Farmers)

  • 정학균;문동현
    • 한국유기농업학회지
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    • 제21권2호
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    • pp.139-155
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    • 2013
  • The purpose of this study is to analyze the effects of abolishing the low-pesticide agricultural product certification on environmentally friendly farming. A survey was conducted to quantitatively analyze farming practices and factors that change farming practice. It was found that only 17.0% of low-pesticide fruit farmers said that they will change their farming practice into organic or pesticide-free farming. With regard to the factors of farming practice change, binomial logistic regression model was applied for the analysis. In the analysis, it was found that farmers who grow the low-pesticide agricultural product are more likely to change their farming practice into organic or pesticide-free farming, as their expected price of organic or pesticide-free products is high, their area size is small, price premium of low-pesticide agricultural product is low, the frequency of their training is high. It is necessary to enhance the direct payment system to enlarge organic and nonpesticide acreage, and pest management techniques for fruits should be developed for low-pesticide fruit farmers to change their practice into organic and nonpesticide practice. Dissemination of cultivation manual, introduction of insurance to farmers, improvement of certificate system, and advertising and marketing of environment-friendly agricultural products are useful to develop environment-friendly agriculture.

On statistical Computing via EM Algorithm in Logistic Linear Models Involving Non-ignorable Missing data

  • Jun, Yu-Na;Qian, Guoqi;Park, Jeong-Soo
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 추계 학술발표회 논문집
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    • pp.181-186
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    • 2005
  • Many data sets obtained from surveys or medical trials often include missing observations. When these data sets are analyzed, it is general to use only complete cases. However, it is possible to have big biases or involve inefficiency. In this paper, we consider a method for estimating parameters in logistic linear models involving non-ignorable missing data mechanism. A binomial response and normal exploratory model for the missing data are used. We fit the model using the EM algorithm. The E-step is derived by Metropolis-hastings algorithm to generate a sample for missing data and Monte-carlo technique, and the M-step is by Newton-Raphson to maximize likelihood function. Asymptotic variances of the MLE's are derived and the standard error and estimates of parameters are compared.

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로지스틱모형에서 그래픽을 이용한 회귀와 모형평가 (Graphical regression and model assessment in logistic model)

  • 강명욱;김부용;홍주희
    • Journal of the Korean Data and Information Science Society
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    • 제21권1호
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    • pp.21-32
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    • 2010
  • 그래픽적 회귀는 모형에 대한 가정을 하지 않고 회귀정보를 모두 포함하는 충분요약그림을 찾아내는 분석 방법으로 모든 회귀정보를 저차원의 그림으로 표현할 수 있게 하는 데에 그 목적이 있다. 잔차산점도를 이용한 모형의 평가는 적용 범위가 선형회귀모형에 국한되는 문제점이 있기 때문에 일반화선형모형에서는 그 대안으로 주변모형 산점도를 이용하여 모형의 적절성을 평가한다. 본 논문에서는 일반화선형모형 중에서 이진반응변수를 갖는 로지스틱모형에서의 그래픽적 회귀 방법과 주변모형 산점도를 이용한 모형평가 방법을 알아본다.

Goodness-of-fit tests for a proportional odds model

  • Lee, Hyun Yung
    • Journal of the Korean Data and Information Science Society
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    • 제24권6호
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    • pp.1465-1475
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    • 2013
  • The chi-square type test statistic is the most commonly used test in terms of measuring testing goodness-of-fit for multinomial logistic regression model, which has its grouped data (binomial data) and ungrouped (binary) data classified by a covariate pattern. Chi-square type statistic is not a satisfactory gauge, however, because the ungrouped Pearson chi-square statistic does not adhere well to the chi-square statistic and the ungrouped Pearson chi-square statistic is also not a satisfactory form of measurement in itself. Currently, goodness-of-fit in the ordinal setting is often assessed using the Pearson chi-square statistic and deviance tests. These tests involve creating a contingency table in which rows consist of all possible cross-classifications of the model covariates, and columns consist of the levels of the ordinal response. I examined goodness-of-fit tests for a proportional odds logistic regression model-the most commonly used regression model for an ordinal response variable. Using a simulation study, I investigated the distribution and power properties of this test and compared these with those of three other goodness-of-fit tests. The new test had lower power than the existing tests; however, it was able to detect a greater number of the different types of lack of fit considered in this study. I illustrated the ability of the tests to detect lack of fit using a study of aftercare decisions for psychiatrically hospitalized adolescents.

Analyzing Consumer Behavior in Responses to Delivery Fees in the Chicken Delivery Market: A Survey-Based Approach

  • MyungJoon MOON;Seon-Woong KIM;HongSeok SEO
    • Asian Journal of Business Environment
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    • 제14권2호
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    • pp.31-40
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    • 2024
  • Purpose: This study aims to explore the factors affecting the willingness to pay for chicken delivery services targeting college students. The results of this study provide insights for improving food delivery market services and developing effective marketing strategies. Research design, data and methodology: A survey employing a questionnaire was administered to students at Chungbuk National University over a 10-day period from May 15 to May 24, 2023. Out of 232 distributed surveys, 218 were considered suitable for analysis. Binomial logistic regression analysis was conducted with the willingness to pay for delivery fees contingent on chicken price, serving as the dependent variable. Results: The main findings are following. First, as the price of chicken increases, the percentage of individuals willing to pay more than 2,000 won for delivery services decreases. Second, regardless of chicken price, males exhibit a lower tendency to bear higher delivery service fees compared to females. Lastly, those who lack awareness of their recent delivery fees or have previously paid charges exceeding 3,000 won demonstrate a greater propensity to pay higher delivery service fees compared to those who have paid fees below 3,000 won. Conclusions: It is essential for chicken sellers to identify key customer segments such as single-person households, and offer pricing and services tailored to their needs and preferences.

농촌 공정관광의 재참여 결정요인 (Determinants of Re-participation for Rural Responsible Tourism)

  • 김경희;이선민
    • 한국지역사회생활과학회지
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    • 제27권1호
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    • pp.67-81
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    • 2016
  • Responsible tourism has become an established area of the tourism industry. This study aims to identify the factors that influence re-participation in responsible tourism in rural Korea. On-site survey was conducted on 436 tourists by seven responsible tourism agencies in Korea. The motivation for responsible tourists was categorized into seven types: family togetherness, escape and relaxation, personal growth, social interaction, various experiences, learning, and natural experience. The estimation of a binary logistic regression model determined the characteristics of responsible tourists who are most likely to opt for re-participation in responsible tourism. Results indicated that important factors for re-participation in responsible tourism were 'age', 'educational level', 'accompany', 'length of stay', and 'motivation'. The results implied that tourists' internal and external factors are important for re-participation in responsible tourism. It is expected that this study will contribute to the market expansion of responsible tourism.