• Title/Summary/Keyword: Negative Binomial Model

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On the Extension of Test Statistics for Detecting Negative Binomial Departures from the Poisson Assumption (포아송으로부터 부의 이항분포로의 이탈에 대한 검정통계량의 확장)

  • 이선호
    • Journal of the Korean Statistical Society
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    • v.22 no.2
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    • pp.171-190
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    • 1993
  • 포아송분포로부터 부의 이항분포로의 이탈을 검색하는 통계량들이 자료의 형태에 따라 여러가지 제시되었다. 그런데 대립가설인 부의 이항분포의 모수화 방법에 따라 분산과 평균의 구조가 변하고 국소 최적 검정 통계량도 달라진다는 것이 알려졌다. 본 논문에서는 대립가설을 일반적인 포아송 혼합분포로까지 확장시키고, 일반적인 형태의 분산과 평균의 구조에도 검정 가능한 새로운 통계량 L을 소개하고 있다. 또한 L 통계량은 포아송 분포로부터 부의 이항분포로의 이탈을 다루는 기존의 여러 통계량들의 일반화된 형태임을 보였다. 점근적 상대효율과 모의 실험을 통하여 L 통계량과 기존의 통계량들을 비교한 결과 분산과 평균사이의 구조에 상관없이 L 통계량이 우수한 것임을 입증하였다.

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Measuring Recreational Benefits of Chilgap Reservoir Using TCM (TCM을 이용한 칠갑저수지의 레크리에이션 편익 분석)

  • Hong, Seungjee;Kim, Dae-Sik
    • Journal of Korean Society of Rural Planning
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    • v.22 no.3
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    • pp.97-106
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    • 2016
  • The study attempts to estimate the recreational benefits of Chilgap multi-purpose reservoir using the on-site survey sample of 130 visitors. The individual travel cost method is used for measuring the recreational benefits of Chilgap multi-purpose reservoir and a zero-truncated negative binomial model is used to elicit the travel demand function. The price elasticities of visit demand are ranged from 0.29 to 0.39. Recreational benefits are ranged from 119 to 156 thousand won per visit and are ranged from 292 to 383 thousand won per annual. When the number of annual visitors to Chilgap reservoir is appled, then the recreational benefits are ranged from 2.7 to 3.6 billion won. This study could contribute to the advancement of post-construction evaluation in the public construction field similar to Chilgap reservoir.

Traffic Accident Models of 3-Legged Signalized Intersections in the Case of Cheongju (3지 신호교차로의 교통사고 발생모형 - 청주시를 사례로 -)

  • Park, Byung-Ho;Han, Sang-Uk;Kim, Tae-Young
    • Journal of the Korean Society of Safety
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    • v.24 no.2
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    • pp.94-99
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    • 2009
  • This study deals with the traffic accidents at the 3-legged signalized intersections in Cheongu. The goals are to analyze the geometric, traffic and operational conditions of intersections and to develop a various functional forms that predict the accidents. The models are developed through the correlation analysis, the multiple linear, the multiple nonlinear, Poisson and negative binomial regression analysis. In this study, two multiple linear, two multiple nonlinear and two negative binomial regression models were calibrated. These models were all analyzed to be statistically significant. All the models include 2 common variables(traffic volume and lane width) and model-specific variables. These variables are, therefore, evaluated to be critical to the accident reduction of Cheongju.

Analysis of Food Poisoning via Zero Inflation Models

  • Jung, Hwan-Sik;Kim, Byung-Jip;Cho, Sin-Sup;Yeo, In-Kwon
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.859-864
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    • 2012
  • Poisson regression and negative binomial regression are usually used to analyze counting data; however, these models are unsuitable for fit zero-inflated data that contain unexpected zero-valued observations. In this paper, we review the zero-inflated regression in which Bernoulli process and the counting process are hierarchically mixed. It is known that zero-inflated regression can efficiently model the over-dispersion problem. Vuong statistic is employed to compare performances of the zero-inflated models with other standard models.

Asymptotic distribution of estimator in INAR(1) process with negative binomial marginal (주변분포가 음이항 분포를 따르는 INAR(1)모형에서 추정량의 점근분포)

  • 김희영;박유성
    • The Korean Journal of Applied Statistics
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    • v.9 no.1
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    • pp.111-124
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    • 1996
  • In this paper, we consider the first-order integer valued autoregressive(INAR(1)) model where correlation structure is similar to that of the continuous valued AR(1) process. Several methods for estimating the parameters of the INAR(1) process with negative binomial marginal are discussed. We derive asymptotic distributions of these estimators. The results of a simulation study for these estimators methods show that the estimator which we present in this paper is better than the estimator which Klimko and Nelson(1978) presented. As an application we considered the estimator of M/M/1 queue length.

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A Study on Impact of Factors Influencing Maritime Freight Rates Using Poisson and Negative Binomial Regression Analysis on Blank Sailings of Shipping Companies (포아송 및 음이항 회귀분석을 이용한 해상운임 결정요인이 해운선사의 블랭크 세일링에 미치는 영향 분석 연구)

  • Won-Hyeong Ryu;Hyung-Sik Nam
    • Journal of Navigation and Port Research
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    • v.48 no.1
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    • pp.62-77
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    • 2024
  • In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

Accident Models of Rotary by Vehicle Type (차량유형별 로터리 사고모형)

  • Han, Su-San;Park, Byeong-Ho
    • Journal of Korean Society of Transportation
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    • v.29 no.6
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    • pp.67-74
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    • 2011
  • This study deals with the traffic accidents data from the Korean rotaries (circular intersections) to verify their characteristics affected by different vehicle types. This paper categorized the data into three groups based on vehicle types, and developed a set of accident models. The paper proposed two ZIP models and one negative binomial model through a statistical analysis for three vehicle types: automobile, truck and van, and others. The differences among those models were then statistically compared.

Development of Roundabout Accident Models by Region (지역별 회전교차로 사고모형 개발 및 논의)

  • Son, Seul Ki;Park, Byung Ho
    • International Journal of Highway Engineering
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    • v.20 no.2
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    • pp.67-74
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    • 2018
  • PURPOSES : The goal of this study is the development of roundabout accident models for urban and non-urban areas. METHODS : This study performed a comparative analysis of the regional factors affecting accidents. Traffic accident data were collected for the period 2010~2014 from the TAAS data set of the Road Traffic Authority. To develop the roundabout accident models, the Poisson and negative binomial regression models were used. A total of 25 explanatory variables such as geometry, and traffic volume were used. RESULTS : The key findings are as follows: First, it was found that the null hypotheses that the number of accidents is the same should be rejected. Second, three Poisson regression accident models, which are statistically significant (${\rho}^2$ of 0.154 and 0.385) were developed. Third, it was noted that although the common variable of the three models (models I~III) is the number of entry lanes, the specific variables are entry lane width, roundabout sign, number of circulatory roadways, splitter island, number of exit lanes, exit lane width, number of approach roads, and truck apron. CONCLUSIONS : The results of this study can provide suggestive countermeasures for decreasing the number of roundabout accidents.

Pedestrian Accident Severity Analysis and Modeling by Arterial Road Function (간선도로 기능별 보행사고 심각도 분석과 모형 개발)

  • Beck, Tea Hun;Park, Min kyu;Park, Byung Ho
    • International Journal of Highway Engineering
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    • v.16 no.4
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    • pp.111-118
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    • 2014
  • PURPOSES: The purposes are to analyze the pedestrian accident severity and to develop the accident models by arterial road function. METHODS: To analyze the accident, count data and ordered logit models are utilized in this study. In pursuing the above, this study uses pedestrian accident data from 2007 to 2011 in Cheongju. RESULTS : The main results are as follows. First, daytime, Tue.Wed.Thu., over-speeding, male pedestrian over 65 old are selected as the independent variables to increase pedestrian accident severity. Second, as the accident models of main and minor arterial roads, the negative binomial models are developed, which are analyzed to be statistically significant. Third, such the main variables related to pedestrian accidents as traffic and pedestrian volume, road width, number of exit/entry are adopted in the models. Finally, Such the policy guidelines as the installation of pedestrian fence, speed hump and crosswalks with pedestrian refuge area, designated pedestrian zone, and others are suggested for accident reduction. CONCLUSIONS: This study analyzed the pedestrian accident severity, and developed the negative binomial accident models. The results of this study expected to give some implications to the pedestrian safety improvement in Cheongju.

Bayesian Analysis for the Zero-inflated Regression Models (영과잉 회귀모형에 대한 베이지안 분석)

  • Jang, Hak-Jin;Kang, Yun-Hee;Lee, S.;Kim, Seong-W.
    • The Korean Journal of Applied Statistics
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    • v.21 no.4
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    • pp.603-613
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    • 2008
  • We often encounter the situation that discrete count data have a large portion of zeros. In this case, it is not appropriate to analyze the data based on standard regression models such as the poisson or negative binomial regression models. In this article, we consider Bayesian analysis for two commonly used models. They are zero-inflated poisson and negative binomial regression models. We use the Bayes factor as a model selection tool and computation is proceeded via Markov chain Monte Carlo methods. Crash count data are analyzed to support theoretical results.