• Title/Summary/Keyword: 선형 모형

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15대 국회의원 소속별 의석예측에 대한 대수선형모형

  • 이재창;전명식;정형철
    • Communications for Statistical Applications and Methods
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    • v.4 no.1
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    • pp.65-74
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    • 1997
  • 1996년 15대 국회의원 선거의 소속별 예측의석수와 실제의석수에 대한 정방형 분할표를 구하여 적절한 대수선형모형을 적합시키고 모형의 해석을 시도하였다.

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Analyzing financial time series data using the GARCH model (일반 자기회귀 이분산 모형을 이용한 시계열 자료 분석)

  • Kim, Sahm;Kim, Jin-A
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.3
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    • pp.475-483
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    • 2009
  • In this paper we introduced a class of nonlinear time series models to analyse KOSPI data. We introduce the Generalized Power-Transformation TGARCH (GPT-TGARCH) model and the model includes Zakoian (1993) and Li and Li (1996) models as the special cases. We showed the effectiveness and efficiency of the new model based on KOSPI data.

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A Three-Dimensional Nonlinear Galerkin-FEM Model (비선형 Galerkin-FEM 모형 개발)

  • 강관수;정경태;선우중호
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.7 no.1
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    • pp.33-45
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    • 1995
  • This paper as a sequel to Kang et al. (1994) describes the development of a three-dimensional nonlinear Galerkin-FEM model. Nonlinear advective terms have been incorporated in a manner used by Lardner and Song (1992), that is, using velocities at given nodes computed with linear Galerkin FEM model. The Proposed model is computationally more efficient than previous nonlinear Galerkin models developed by Owen (1980) and Davies (1980) because the model uses a linear shape function as a basis and, furthermore, the similarity transform technique developed by Kang (1994). Two experiments have been carried out to examine effects of nonlinear terms. One is an experiment of wind-driven current in a rectangular basin (Heaps' basin) and the other is an experiment concerning eddy generation behind a jetty with specified downstream and upstream open boundary conditions. The computed Pattern was found to be in good agreement qualitatively with previous model experiments by Stelling (1984).

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Traffic Accident Prediction Model by Freeway Geometric Types (고속도로 선형조건별 교통사고 위험도 평가모형 개발 (호남고속도로를 중심으로))

  • 강정규;이성관
    • Journal of Korean Society of Transportation
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    • v.20 no.4
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    • pp.163-175
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    • 2002
  • Fatalities from traffic accidents constitute one of the major health issues as well as safety ones in Korea. It has been reported that traffic accident is affected by the combined effects of road. vehicle. and human factors. Over the past few decades, a number of studies have been conducted to find the impact of road geometric factors on traffic safety. The purpose of this study is to investigate the effect of road geometric factors on traffic safety on Korean expressways. Detailed geometric design data were available from Korea Highway Corporation. Five-year traffic accident data on Honam expressway were collected and analyzed. It was found that following geometric factors influence traffic safety on expressways : radius of curve, curve length, and length of straight section. Furthermore, the existence of I.C. turned out to have a significant impact on traffic safety level. Based on the data analysis several multiple regression forms that relate traffic accident frequencies and geometric factors on expressways are developed.

Comparing the performance of likelihood ratio test and F-test for gamma generalized linear models (감마 일반화 선형 모형에서의 가능도비 검정과 F-검정 비교연구)

  • Jo, Seongil;Han, Jeongseop;Lee, Woojoo
    • The Korean Journal of Applied Statistics
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    • v.31 no.4
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    • pp.475-484
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    • 2018
  • Gamma generalized linear models are useful for non-negative and skewed responses. However, these models have received less attention than Poisson and binomial generalized linear models. In particular, hypothesis testing for the significance of regression coefficients has not been thoroughly studied. In this paper we assess the performance of various test statistics for gamma generalized linear models based on numerical studies. Our results show that the likelihood ratio test and F-type test are generally recommended and that the partial deviance test should be avoided in practice.

Development of Finite Difference Model for Tsunami Propagation (지진해일 전파모의를 위한 유한차분모형 개발)

  • Ahn, Seong-Ho;Ha, Tae-Min;Cho, Yong-Sik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.52-56
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    • 2010
  • 본 연구에서는 지진해일의 전파 과정을 모의함에 있어 선형 천수방정식의 수치분산을 이용하는 기법이 아닌 선형 Boussinesq 방정식을 직접 차분하는 유한차분기법을 제안하였다. 지배방적식과 차분식의 일치성을 해석하기 위해 이산화 오차를 확인하고, 수치해의 안정적 수렴여부를 판단하기 위해 Von neumann 안정성 해석을 수행하였다. 또한 기법의 정확성을 검증하기 위하여 Gauss 분포의 초기 자유수면변위를 갖는 문제에 적용하여 선형 Boussinesq 방정식의 해석해와 비교하였다. 그 결과 기존의 선형 천수방정식을 차분화한 수치모형에 비하여 정확한 결과를 제공하였고 분산보정기법을 이용한 수치모형과 동일한 정확도를 보였으나 본 수치모형을 이용했을 때 비교적 넓은 범위의 조건에서 정확도 높은 결과를 제공하였다.

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A comparison of formulas to predict a team's winning percentage in Korean pro-baseball (한국프로야구에서 승률 추정방법들의 비교)

  • Lee, Jang Taek
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.6
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    • pp.1585-1592
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    • 2016
  • Estimation of winning percentage in baseball has always been particularly interesting to many baseball fans. We have fitted models including linear regression and Pythagorean formula to the Korean baseball data of seasons from 1982 to 2015. Using RMSE criterion for both the linear formula and the Pythagorean formula, we compared two models in predicting the actual winning percentage. Pythagorean expectation is superior to linear formula when there is either high or low winning percentage. Two methods yield very similar efficiencies when the actual winning percentage is about 50%. To understand and use for estimating winning percentage, it is easier linear formula as estimated equations.

Bayesian Variable Selection in Linear Regression Models with Inequality Constraints on the Coefficients (제한조건이 있는 선형회귀 모형에서의 베이지안 변수선택)

  • 오만숙
    • The Korean Journal of Applied Statistics
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    • v.15 no.1
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    • pp.73-84
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    • 2002
  • Linear regression models with inequality constraints on the coefficients are frequently used in economic models due to sign or order constraints on the coefficients. In this paper, we propose a Bayesian approach to selecting significant explanatory variables in linear regression models with inequality constraints on the coefficients. Bayesian variable selection requires computation of posterior probability of each candidate model. We propose a method which computes all the necessary posterior model probabilities simultaneously. In specific, we obtain posterior samples form the most general model via Gibbs sampling algorithm (Gelfand and Smith, 1990) and compute the posterior probabilities by using the samples. A real example is given to illustrate the method.

Hydraulic Flood Routing using Linear Reservoir Model (선형저수지모형을 적용한 수리학적 홍수추적)

  • Jeon, Min-Woo;Cho, Young-Soo
    • Journal of Korea Water Resources Association
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    • v.35 no.6
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    • pp.787-796
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    • 2002
  • Hydraulic flood routing was performed for unsteady flow in a natural river using Preissmann scheme. A Log-Pearson Type-Ⅲ hydrograph is chosen arbitrarily as the upstream boundary condition and lateral inflow hydrographs for sensitivity analysis. For the application with an actual river system, upstream and lateral inflow hydrographs were estimated by the linear reservoir model and the Manning's equation was used as the downstream boundary condition. The unsteady flow model using the linear reservoir model as the inflow hydrographs was applied to Bochung stream basin and gives good results, and is approved to be used for the runoff prediction. As results of the sensitivity analysis, the proposed model may help to estimate the roughness coefficients when using the unsteady flow model with lateral inflow combined with the linear reservoir model.

A linearity test statistic in a simple linear regression (단순회귀모형에서 선형성 검정통계량)

  • Park, Chun Gun;Lee, Kyeong Eun
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.2
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    • pp.305-315
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    • 2014
  • In a simple linear regression, a linear relationship between an explanatory variable and a response variable can be easily recognized in the scatter plot of them. The lack of fit test for the replicated data is commonly used for testing the linearity but it is not easy to test the linearity when the explanatory variable is not replicated. In this paper, we propose three new test statistics for testing the linearity regardless of replication using the principle of average slope and validate them through several simulations and empirical studies.