• Title/Summary/Keyword: 일반화 이항모형

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Comparative Simulation Studies on Generalized Binomial Models (일반화 이항모형의 적합도 평가)

  • Baik, E.J.;Kim, K.Y.
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.507-516
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    • 2011
  • Comparative studies on generalized binomial models (Moon, 2003; Ng, 1989; Paul, 1985; Kupper and Haseman, 1978; Griffiths, 1973) are restrictive in that the models compared are rather limited and MSE of the estimates is the only measure considered for the model adequacy. This paper is aimed to report simulation results which provide possible guidelines for selecting a proper model. We examine Pearson type of goodness-of-fit statistic to its degrees of freedom and AIC for the overall model quality. MSE and Bias of the individual estimates are also considered as the component fit measures. Performance of some models varies widely for a certain range of the parameter space while most of the models are quite competent. Our evaluation shows that the Extended Beta-Binomial model (Prentice, 1986) turns out to be particularly favorable in the point that it provides consistently excellent fit almost all over the values of the intra-class correlation coefficient and the probability of success.

Fitting Bivariate Generalized Binomial Models of the Sarmanov Type (Sarmanov형 이변량 일반화이항모형의 적합)

  • Lee, Joo-Yong;Kim, Kee-Young
    • The Korean Journal of Applied Statistics
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    • v.22 no.2
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    • pp.271-280
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    • 2009
  • For bivariate binomial data with both intra and inter-class correlation, Danaher and Hardie (2005) proposed a bivariate beta-binomial model. However, the model is limited to the situation where the intra-class correlation is strictly positive. Thus it might be seriously inadequate for data with a negative intra-class correlation. Several authors have considered generalized binomial distributions covering a wider range of intra-class correlation which could relax the possible model restrictions imposed. Among others there are the additive/multiplicative and the beta/extended beta binomial model. In this study, bivariate models of the Sarmanov (1966) type are formed by combining each of those univariate models to take care of the inter-class correlation, and are evaluated in terms of the goodness-of-fit. As a result, B-mB and B-ebB are fitted, successfully, to real data and that B-mB, which has a wider permissible range than B-ebB for the intra-class correlation is relatively preferred.

Comparison of Estimators of Dependence Related Parameter in Generalized Binomial Distribution (일반화 이항분포모형에서 시행간 종속성 규정모수의 추정량 비교 연구)

  • Moon, Myung-Sang
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.2
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    • pp.279-288
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    • 1999
  • In many cases where the conventional binomial distribution fails to apply to real world data, it is mainly due to the lack of independence among Bernoulli trials. Several authors have proposed models that are useful when independence assumption is not satisfied. In this paper, one proposed model is adapted, and estimators of dependence related parameter that is crucial in defining that model are considered. Simulation is performed to compare two estimators(method of moment estimator and maximum likelihood estimator) of dependence related parameter, and conclusions are made.

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Barrier Option Pricing with Binomial Trees Applying Generalized Catalan Numbers (이항분포모형에 일반화된 카탈란 수를 적용한 배리어 옵션의 가격 산정)

  • Choi, Seung-il
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.12
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    • pp.226-231
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    • 2016
  • Binomial trees are used to price barrier options. Since barrier options are path dependent, option values of each node are calculated from binomial trees using backward induction. We use generalized Catalan numbers to determine the number of cases not reaching a barrier. We will generalize Catalan numbers by imposing upper and lower bounds. Reaching a barrier in binomial trees is determined by the difference between the number of up states and down states. If we count the cases that the differences between the up states and down states remain in a specific range, the probability of not reaching a barrier is obtained at a final node of the tree. With probabilities and option values at the final nodes of the tree, option prices are computable by discounting the expected option value at expiry. Without calculating option values in the middle nodes of binomial trees, option prices are computable only with final option values. We can obtain a probability distribution of exercising an option at expiry. Generalized Catalan numbers are expected to be applicable in many other areas.

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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Comparing the efficiency of dispersion parameter estimators in gamma generalized linear models (감마 일반화 선형 모형에서의 산포 모수 추정량에 대한 효율성 연구)

  • Jo, Seongil;Lee, Woojoo
    • The Korean Journal of Applied Statistics
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    • v.30 no.1
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    • pp.95-102
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    • 2017
  • Gamma generalized linear models have received less attention than Poisson and binomial generalized linear models. Therefore, many old-established statistical techniques are still used in gamma generalized linear models. In particular, existing literature and textbooks still use approximate estimates for the dispersion parameter. In this paper we study the efficiency of various dispersion parameter estimators in gamma generalized linear models and perform numerical simulations. Numerical studies show that the maximum likelihood estimator and Cox-Reid adjusted maximum likelihood estimator are recommended and that approximate estimates should be avoided in practice.

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.

Parameter Estimation of Auto-Binomial Model using Selectionist Relaxation for Segmentation of Texture Images (유전자적 완화법에 의한 자기이항모형의 파라미터 추정과 질감 영상분할)

  • Lee, Seung-U;Kim, Hwang-Su;Park, Yeong-Cheol
    • Journal of KIISE:Software and Applications
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    • v.28 no.3
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    • pp.298-304
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    • 2001
  • Markov 랜덤 필드(MRF)를 이용한 질감 영상의 영역분할을 각 영역을 기술해줄 수 있는 제대로 된 파라미터들을 찾는 것이 가장 중요하다. 종래에는 입력영상의 질감 영역의 수와 그 형태 등을 초기에 적당히 가정하여 파라미터를 찾는 방법을 써왔는데 실제 영상에는 잘 맞지 않았다. 최근에 완화법(Relaxation)을 이용하여 MRF의 파라미터를 찾는 방법이 제안[8]되었는데 오직 일반화된 Ising 모형에서만 사용가능 하였다. 본 논문에서는 비교적 자연영상에 적합한 자기이항 모형(Auto-binomial Model)에 변형된 완화법을 적용시켜 파라미터를 추정하고 질감 영상을 분할해 보았다. 그 결과 이전의 Ising 모형으로는 어려웠던 자연영산의 분할에서 좋은 결과를 얻을 수 있었다.

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

  • Kahng, Myung-Wook;Kim, Bu-Yong;Hong, Ju-Hee
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.1
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    • pp.21-32
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    • 2010
  • Graphical regression is a paradigm for obtaining regression information using plots without model assumptions. The general goal of this approach is to find lowdimensional sufficient summary plots without loss of important information. Model assessments using residual plots are less likely to be successful in models that are not linear. As an alternative approach, marginal model plots provide a general graphical method for assessing the model. We apply the methods of graphical regression and model assessment using marginal model plots to the logistic regression model.

The Effects of Dispersion Parameters and Test for Equality of Dispersion Parameters in Zero-Truncated Bivariate Generalized Poisson Models (제로절단된 이변량 일반화 포아송 분포에서 산포모수의 효과 및 산포의 동일성에 대한 검정)

  • Lee, Dong-Hee;Jung, Byoung-Cheol
    • The Korean Journal of Applied Statistics
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    • v.23 no.3
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    • pp.585-594
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    • 2010
  • This study, investigates the effects of dispersion parameters between two response variables in zero-truncated bivariate generalized Poisson distributions. A Monte Carlo study shows that the zero-truncated bivariate Poisson and negative binomial models fit poorly wherein the zero-truncated bivariate count data has heterogeneous dispersion parameters on dependent variables. In addition, we derive the score test for testing the equality of the dispersion parameters and compare its efficiency with the likelihood ratio test.