• Title/Summary/Keyword: 확률적 회귀모형

Search Result 184, Processing Time 0.025 seconds

The Effect of Part-time Work on the Satisfaction of Personal Life - Using Seoul Survey - (시간제 근로 및 성별에 따른 개인의 삶의 만족도 분석 - 「서울서베이 도시정책지표조사」를 이용하여 -)

  • Kim, Jae Won;Lim, Up
    • Journal of the Korean Regional Science Association
    • /
    • v.35 no.2
    • /
    • pp.59-71
    • /
    • 2019
  • Korea's average annual working hours are among the highest in the OECD. Such long-term work has been a factor that reduces the quality of life by discouraging workers' productivity and interrupting the compatibility of work and family, prompting the government to encourage flexible work systems, such as increasing part-time jobs, but a lack of quality part-time jobs. Part-time work enables flexible labor for workers, but at the same time, workers will involuntarily opt for part-time work as they have poor working conditions and negative social views. In this respect, the effect of the working type on an individual's life is expected to be different. In addition, for women, gender gaps exist in the labor market and the impact of part-time work on life satisfaction is expected to differ from men in terms of working and family alike. Using the data from the 2017 "Seoul Survey Urban Policy Indicator Survey", the ordered logistic regression model was used to analyze the cross-effect of working type and sex on satisfaction. The analysis of the study showed that when other factors were controlled, life satisfaction was high in the order of fulltime female, full-time male, part-time female, and part-time male. In addition, further analysis shows that the parttime female workers have the highest probability of choosing low life satisfaction, while the probability of choosing high life satisfaction is the lowest, and full-time male workers have the lowest probability of choosing low life satisfaction, while the highest probability of choosing high life satisfaction is the highest.

Development of algorithm for analyzing priority area of forest fire surveillance using viewshed analysis (가시권 분석을 이용한 산불감시 우선지역 분석체계 개발)

  • Lee, Byung-Doo;Kim, Seon-Young;Lee, Myung-Bo
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
    • /
    • 2010.06a
    • /
    • pp.173-174
    • /
    • 2010
  • 산불감시활동에 의한 탐지확률을 높이고, 감시자원의 효율적인 이용을 위해서는 산불 감시 우선지역에 대한 분석이 요구된다. 따라서 산불감시 우선지역을 추출하기 위해 가시권 분석과 산불발생확률 분석을 실시하였으며, 중첩을 통해 가중치를 부여하였다. 가시권 분석은 탐지확률과 관련된 감시자원의 높이, 산불연기높이, 지형의 roughness에 따른 유효가시거리 인자를 다르게 하여 실시하였다. 산불발생확률은 로지스틱 회귀분석모형과 연료, 기상, 지형인자 및 토지피복, 접근성 인자 DB를 이용하여 분석하였다. 개발된 산불감시 우선지역 분석체계는 산불감시자원의 효율성 제고를 위한 기초자료로 활용될 수 있을 것으로 예상되었다.

  • PDF

Development of a Logistic Regression Model for Probabilistic Prediction of Debris Flow (토석류 산사태 예측을 위한 로지스틱 회귀모형 개발)

  • 채병곤;김원영;조용찬;김경수;이춘오;최영섭
    • The Journal of Engineering Geology
    • /
    • v.14 no.2
    • /
    • pp.211-222
    • /
    • 2004
  • In this study, a probabilistic prediction model for debris flow occurrence was developed using a logistic regression analysis. The model can be applicable to metamorphic rocks and granite area. order to develop the prediction model, detailed field survey and laboratory soil tests were conducted both in the northern and the southern Gyeonggi province and in Sangju, Gyeongbuk province, Korea. The seven landslide triggering factors were selected by a logistic regression analysis as well as several basic statistical analyses. The seven factors consist of two topographic factors and five geological and geotechnical factors. The model assigns a weight value to each selected factor. The verification results reveal that the model has 90.74% of prediction accuracy. Therefore, it is possible to predict landslide occurrence in a probabilistic and quantitative manner.

Design and Implementation of Trip Generation Model Using the Bayesian Networks (베이지안 망을 이용한 통행발생 모형의 설계 및 구축)

  • Kim, Hyun-Gi;Lee, Sang-Min;Kim, Kang-Soo
    • Journal of Korean Society of Transportation
    • /
    • v.22 no.7 s.78
    • /
    • pp.79-90
    • /
    • 2004
  • In this study, we applied the Bayesian Networks for the case of the trip generation models using the Seoul metropolitan area's house trip survey Data. The household income was used for the independent variable for the explanation of household size and the number of cars in a household, and the relationships between the trip generation and the households' social characteristics were identified by the Bayesian Networks. Furthermore, trip generation's characteristics such as the household income, household size and the number of cars in a household were also used for explanatory variables and the trip generation model was developed. It was found that the Bayesian Networks were useful tool to overcome the problems which were in the traditional trip generation models. In particular the various transport policies could be evaluated in the very short time by the established relationships. It is expected that the Bayesian Networks will be utilized as the important tools for the analysis of trip patterns.

A Bayesian Regression Model to Estimate the Deterioration Rate of Track Irregularities (궤도틀림 진전율 추정을 위한 베이지안 회귀분석 모형 연구)

  • Park, Bum Hwan
    • Journal of the Korean Society for Railway
    • /
    • v.19 no.4
    • /
    • pp.547-554
    • /
    • 2016
  • This study considered how to estimate the deterioration rate of the track quality index, which represents track geometric irregularity. Most existing studies have used a simple linear regression and regarded the slope of the regression equation as the progress rate. In this paper, we present a Bayesian approach to estimate the track irregularity progress. This Bayesian approach has many advantages, among which the biggest is that it can formally include the prior distribution of parameters which can be derived from historic data or from expert experiences; then, the rate can be expressed as a probability distribution. We investigated the possibility of applying the Bayesian method to the estimation of the deterioration rate by comparing our bayesian approach to the conventional linear regression approach.

A Study on Job Satisfaction and Turnover Behavior with 2-Stage Logistic Regression: In Case of Graduates Occupational Mobility Survey (2단계 로지스틱 회귀모형을 이용한 직무만족도와 이직행동에 관한 연구 - 대졸자 직업이동 경로조사 자료를 중심으로)

  • Chung, Sung-Suk;Lee, Ki-Hoon
    • Communications for Statistical Applications and Methods
    • /
    • v.15 no.6
    • /
    • pp.859-873
    • /
    • 2008
  • Job satisfaction impacts on the turnover intention of employee, which affects the turnover behavior. This paper concerns with the impact of job satisfaction on the turn over behavior. Since turnover intention is highly correlated with job satisfaction, salary, employment status and etc, we should pay careful attention for modelling of those variables as independent variables and the turnover behavior as a dependent variable in the empirical study for the impact of factors on turnover behavior. We detect significant variables which effect the turnover behavior using 2-stage logistic regression inserting the turnover intention, an independent variable, with the chance estimates derived from the instrumental variables in Graduates Occupational Mobility Survey.

Analysis of Traffic Flow on Weaving Sections Using Stochastic Models (확률모형을 이용한 엇갈림 구간의 교통류분석)

  • 이승준;이정도;최재성
    • Journal of Korean Society of Transportation
    • /
    • v.17 no.5
    • /
    • pp.137-149
    • /
    • 1999
  • For decades, many traffic flow studies on the analysis and determination of level of service (LOS) for the weaving sections have been made to Provide several regression equations. Weaving and non-weaving speeds were dependent variables for the equations, with independent variables being weaving length, number of lanes, and weaving ratios. One of the difficulties in developing the equations was that the weaving areas were rare in Korea, so the statistical analyses for calibrating the equation parameter could not be performed in a desirable manner. In this regard, a new and stochastic methodology for predicting the weaving and non-weaving speeds within the weaving sections was required. In this study the following design variables were developed; influence area of the weaving section. headway distribution within the weaving section, maximum weaving volume of the weaving section, length of the ideal weaving section, and speed estimations for the weaving and non-weaving flows. The evaluation of the new model was made comparing the delay in the weaving section with the one in the freeway basic section.

  • PDF

내구소비재 보유함수의 추정: 이진수 종속변수를 이용한 회귀분석

  • Yoon, Suk Bum;Lee, Hoe Kyung
    • Journal of the Korean Statistical Society
    • /
    • v.6 no.2
    • /
    • pp.117-154
    • /
    • 1977
  • 본논문에서는 첫째로 단일방정식 모형에서 종속변수가 양자택일(binary choice)의 이산확률변수일 때 이러한 이진적 종속변수(binary dependent variable)의 변동을 설명하는데 사용되는 몇 가지 모형을 소개하고 각각의 표기 및 추정방법, 추정량의 성질, 예측 및 검정 문제 등에 관하여 비교 서술하고자 한다. 둘째, 종속변수가 이산과 연속의 혼합형태일 때 앞에 소개된 모형이 어떻게 적용될 수 있는가를 살펴보며, 셋째, 선택대상 및 종속변수의 수가 증가하여 일반화된 선다형모형(multiple choice model)의 경우, 표기 및 추정방법을 단일방정식 기법을 이용하여 추가로 총람하고자 한다. 넷째, 본논문에서는 또한 내구소비재 구입에 관한 조사자료를 이용하여 실제 많이 사용되는 몇 개의 모형을 선택하여 적용하고 각각의 예측력을 분석함으로써 각 모형을 비교 검토하는데 목적이 있다.

  • PDF

Comparison of methods of approximating option prices with Variance gamma processes (Variance gamma 확률과정에서 근사적 옵션가격 결정방법의 비교)

  • Lee, Jaejoong;Song, Seongjoo
    • The Korean Journal of Applied Statistics
    • /
    • v.29 no.1
    • /
    • pp.181-192
    • /
    • 2016
  • We consider several methods to approximate option prices with correction terms to the Black-Scholes option price. These methods are able to compute option prices from various risk-neutral distributions using relatively small data and simple computation. In this paper, we compare the performance of Edgeworth expansion, A-type and C-type Gram-Charlier expansions, a method of using Normal inverse gaussian distribution, and an asymptotic method of using nonlinear regression through simulation experiments and real KOSPI200 option data. We assume the variance gamma model in the simulation experiment, which has a closed-form solution for the option price among the pure jump $L{\acute{e}}vy$ processes. As a result, we found that methods to approximate an option price directly from the approximate price formula are better than methods to approximate option prices through the approximate risk-neutral density function. The method to approximate option prices by nonlinear regression showed relatively better performance among those compared.

A Study on regionalization of PDM model parameters (확률분포모형(PDM)의 매개변수 지역화에 관한 연구)

  • Chang, Hyung Joon;Lee, Hyo Sang;Kim, Seong Goo;Park, Ki Soon
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2017.05a
    • /
    • pp.224-224
    • /
    • 2017
  • 지구온난화로 인한 기후변화 등으로 안전한 하천구조물을 설계하기 위해서는 신뢰할 수 있는 홍수량 산정이 필요하다. 신뢰할 수 있는 홍수량 산정을 위해서는 정도 높은 과거 수문자료가 필요하나 국내의 많은 중소 규모유역이 미계측 유역 또는 과거 수문자료 부족으로 신뢰 할 수 있는 홍수량 산정이 어려운 실정이다. 본 연구에서는 미계측 유역의 홍수량 산정을 위하여 확률분포모형(PDM)의 매개변수 지역화를 수행하였다. 매개변수 지역화 연구를 수행하기 위하여, 금강 25개 유역을 대상으로 유역별 9~18개의 단기홍수수문사상을 선정하였다. 선정된 단기홍수수문사상을 확률분포모형에 적용하기위하여, MCAT (Monte Carlo Analysis Toolbox)을 활용하여 검정 및 검증을 수행하였으며, 목적함수는 수문곡선 모든 구간을 반영하는 NSE (Nash Sutcliffe Efficiency)와 고유량 부분을 반영하는 RMSE (Root Mean Squared Error) - FH를 적용하였다. 각각의 목적함수에 대하여 검정 모형 매개변수와 유역 특성인자의 다중 선형회귀식을 강우유출모형 매개변수 지역화 모형으로 제시하였다. 매개변수 지역화 결과의 평가를 위하여 청주 유역을 미계측 유역으로 가정하였다. 청주 유역에 대하여 지역화 매개변수를 적용한 결과, 17개의 사상 중 11개의 사상에서 NSE 목적함수 값이 0.5이상으로 전체적인 수문곡선의 경향성을 보였으며, 첨두 홍수량은 17개 사상 중 11개 사상에서 관측 첨두 홍수량 값의 20%이내를 제시하여 적합한 결과를 제시하였다. 또한 금강 25개 유역에 Jackknife 방법으로 검정 결과 관측 첨두 홍수량 값 20%이내의 성능을 보이는 사상이 56%를 포함하고 있어 의미있는 지역화 모형을 제시하였다고 판단된다. 본 연구에서 제시한 매개변수 지역화 방법은 미계측 유역의 유출모의에 활용될 수 있음을 확인하였다.

  • PDF