• Title/Summary/Keyword: 이항모형

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Testing for Overdispersion in a Bivariate Negative Binomial Distribution Using Bootstrap Method (이변량 음이항 모형에서 붓스트랩 방법을 이용한 과대산포에 대한 검정)

  • Jhun, Myoung-Shic;Jung, Byoung-Cheol
    • The Korean Journal of Applied Statistics
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    • v.21 no.2
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    • pp.341-353
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    • 2008
  • The bootstrap method for the score test statistic is proposed in a bivariate negative binomial distribution. The Monte Carlo study shows that the score test for testing overdispersion underestimates the nominal significance level, while the score test for "intrinsic correlation" overestimates the nominal one. To overcome this problem, we propose a bootstrap method for the score test. We find that bootstrap methods keep the significance level close to the nominal significance level for testing the hypothesis. An empirical example is provided to illustrate the results.

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.

Development of a p Control Chart for Overdispersed Process with Beta-Binomial Model (베타-이항모형을 이용한 과산포 공정용 p 관리도의 개발)

  • Bae, Bong-Soo;Seo, Sun-Keun
    • Journal of Korean Society for Quality Management
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    • v.45 no.2
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    • pp.209-225
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    • 2017
  • Purpose: Since traditional p chart is unable to deal with the variation of attribute data, this paper proposes a new attribute control chart for nonconforming proportions incorporating overdispersion with a beta-binomial model. Methods: Statistical theories for control chart developed under the beta-binomial model and a new approach using this control chart are presented Results: False alarm probabilities of p chart with the beta-binomial model are evaluated and demerits of p chart under overdispersion are discussed from three examples. Hence a concrete procedure for the proposed control chart is provided and illustrated with examples Conclusion: The proposed chart is more useful than traditional p chart, individual chart to treat observed proportions nonconforming as variable data and Laney p' chart.

A Study on Real Option Valuation for Technology Investment Using the Monte Carlo Simulation (몬테칼로 시뮬레이션을 이용한 기술투자 실물옵션평가에 대한 연구)

  • Sung Oong-Hyun
    • Journal of Korea Technology Innovation Society
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    • v.7 no.3
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    • pp.533-554
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    • 2004
  • Real option valuation considers the managerial flexibility to make ongoing decisions regarding implementation of investment projects and deployment of real assets. The appeal of the framework is natural given the high degree of uncertainty that firms face in their technology investment decisions. This paper suggests an algorithm for estimating volatility of logarithmic cash flow returns of real asset based on Monte Carlo simulation. This research uses a binomial model to obtain point estimate of real option value with embedded expansion option case and provides also an array of numerical results to show the interval estimation of option value using Monte Carlo simulation.

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Count Data Model for The Estimation of Bus Ridership (Focusing on Commuters and Students in Seoul) (가산자료모형(Count Data Model)을 이용한 버스이용횟수추정에 관한 연구 (서울시 통근.통학자를 대상으로))

  • 문진수;김순관;임강원
    • Journal of Korean Society of Transportation
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    • v.17 no.5
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    • pp.123-135
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    • 1999
  • The rapid increase of Passenger cars which is caused by the discomfort of Public transit and the Preference of automobiles is the major factor of increasing traffic congestions in Seoul With the point that leading the automobilists to the Public transit can be the most important Policy to ease these traffic congestions, this study focuses on the behavioral aspects of company employees and university students and investigates factors influencing bus ridership. To be brief, by estimating bus ridership through count models, this study investigates factors which influence bus ridership and elicits Political suggestions which lead automobilists to Public transit. The Purpose in this study is the application of appropriate count data model. The count data models have been widely applied to the economic area from the middle of the 1980s and to transportation aspect mainly in the foreign countries from the latter half of the 1980s. Even though a few studies in this country employed count data model to count data. all of them were Poisson regression models without suitable tests for the importance of the model specification. In the end, as the result of statistical test, negative binomial regression model which is suitable for overdispersed data was found to be appropriate for the data of weekly bus ridership. To emphasize the importance of model specification, both of poisson regression model and negative binomial regression model were estimated and the results were compared.

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Estimation methods and interpretation of competing risk regression models (경쟁 위험 회귀 모형의 이해와 추정 방법)

  • Kim, Mijeong
    • The Korean Journal of Applied Statistics
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    • v.29 no.7
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    • pp.1231-1246
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    • 2016
  • Cause-specific hazard model (Prentice et al., 1978) and subdistribution hazard model (Fine and Gray, 1999) are mostly used for the right censored survival data with competing risks. Some other models for survival data with competing risks have been subsequently introduced; however, those models have not been popularly used because the models cannot provide reliable statistical estimation methods or those are overly difficult to compute. We introduce simple and reliable competing risk regression models which have been recently proposed as well as compare their methodologies. We show how to use SAS and R for the data with competing risks. In addition, we analyze survival data with two competing risks using five different models.

Developing an Accident Model for Rural Signalized Intersections Using a Random Parameter Negative Binomial Method (RPNB모형을 이용한 지방부 신호교차로 교통사고 모형개발)

  • PARK, Min Ho;LEE, Dongmin
    • Journal of Korean Society of Transportation
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    • v.33 no.6
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    • pp.554-563
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    • 2015
  • This study dealt with developing an accident model for rural signalized intersections with random parameter negative binomial method. The limitation of previous count models(especially, Poisson/Negative Binomial model) is not to explain the integrated variations in terms of time and the distinctive characters a specific point/segment has. This drawback of the traditional count models results in the underestimation of the standard error(t-value inflation) of the derived coefficient and finally affects the low-reliability of the whole model. To solve this problem, this study improves the limitation of traditional count models by suggesting the use of random parameter which takes account of heterogeneity of each point/segment. Through the analyses, it was found that the increase of traffic flow and pedestrian facilities on minor streets had positive effects on the increase of traffic accidents. Left turning lanes and median on major streets reduced the number of accidents. The analysis results show that the random parameter modeling is an effective method for investigating the influence on traffic accident from road geometries. However, this study could not analyze the effects of sequential changes of driving conditions including geometries and safety facilities.

Bayesian analysis of cumulative logit models using the Monte Carlo Gibbs sampling (몬테칼로깁스표본기법을 이용한 누적로짓 모형의 베이지안 분석)

  • 오만숙
    • The Korean Journal of Applied Statistics
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    • v.10 no.1
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    • pp.151-161
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    • 1997
  • An easy Monte Carlo Gibbs sampling approach is suggested for Bayesian analysis of cumulative logit models for ordinal polytomous data. Because in the cumulative logit model the posterior conditional distributions of parameters are not given in convenient forms for random sample generation, appropriate latent variables are introduced into the model so that in the new model all the conditional distributions are given in very convenient forms for implementation of the Gibbs sampler.

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An Empirical Study on the Measurement of Clustering and Trend Analysis among the Asian Container Ports Using the Variable Group Benchmarking and Categorical Variable Models (가변 그룹 벤치마킹 모형과 범주형 변수모형을 이용한 아시아 컨테이너항만의 클러스터링측정 및 추세분석에 관한 실증적 연구)

  • Park, Rokyung
    • Journal of Korea Port Economic Association
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    • v.29 no.1
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    • pp.143-175
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    • 2013
  • The purpose of this paper is to show the clustering trend by using the variable group benchmarking(VGB) and categorical variable(CV) models for 38 Asian ports during 9 years(2001-2009) with 4 inputs(birth length, depth, total area, and number of crane) and 1 output(container TEU). The main empirical results of this paper are as follows. First, clustering results by using VGB show that Shanghai, Qingdao, and Ningbo ports took the core role for clustering. Second, CV analysis focusing on the container throughputs indicated that Singapore, Keelong, Dubai, and Kaosiung ports except Chinese ports are appeared as the center ports of clustering. Third, Aqaba, Dubai, Hongkong, Shanghai, Guangzhou, and Ningbo ports are recommended as the efficient ports for the target of clustering. Fourth, when the ports are classified by the regional location, Dubai, Khor Fakkan, Shanghai, Hongkong, Keelong, Ningbo, and Singapore ports are the core ports for clustering. On the whole, other ports located in Asia should be clustered to Dubai, Khor Fakkan, Shanghai, Hongkong, Ningbo, and Singapore ports. The policy implication of this paper is that Korean port policy planner should introduce the VGB model, and CV model for clustering among the international ports for enhancing the efficiency of inputs and outputs.

Analyzing the Characteristics of Traffic Accidents and Developing the Models by Day and Night in the Case of the Cheongju Arterial Link Sections (청주시 간선가로 구간의 주.야간 사고특성 및 모형개발)

  • Kim, Tae-Young;Lim, Jin-Kang;Park, Byung-Ho
    • International Journal of Highway Engineering
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    • v.13 no.1
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    • pp.13-19
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    • 2011
  • The purpose of this study is to analyze the characteristics of traffic accidents and to develop the models by day and night-time in the case of the arterial link sections. In pursuing the above, this study uses the 224 accident data occurred at the 24 arterial link sections in Cheongju. The main results analyzed are as follows. First, it was analyzed that the number of accidents during day was more than night, but the accidents rate during night was higher than day. Second, four models which were all statistically significant were developed. Finally, the differences between the day and night models were comparatively analyzed using independent variables.