• 제목/요약/키워드: Count Data Model

검색결과 229건 처리시간 0.051초

Sire Evaluation of Count Traits with a Poisson-Gamma Hierarchical Generalized Linear Model

  • Lee, C.;Lee, Y.
    • Asian-Australasian Journal of Animal Sciences
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    • 제11권6호
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    • pp.642-647
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    • 1998
  • A Poisson error model as a generalized linear mixed model (GLMM) has been suggested for genetic analysis of counted observations. One of the assumptions in this model is the normality for random effects. Since this assumption is not always appropriate, a more flexible model is needed. For count traits, a Poisson hierarchical generalized linear model (HGLM) that does not require the normality for random effects was proposed. In this paper, a Poisson-Gamma HGLM was examined along with corresponding analytical methods. While a difficulty arises with Poisson GLMM in making inferences to the expected values of observations, it can be avoided with the Poisson-Gamma HGLM. A numerical example with simulated embryo yield data is presented.

A generalized regime-switching integer-valued GARCH(1, 1) model and its volatility forecasting

  • Lee, Jiyoung;Hwang, Eunju
    • Communications for Statistical Applications and Methods
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    • 제25권1호
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    • pp.29-42
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    • 2018
  • We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markov-chain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.

허베이 스피리트호의 기름유출에 따른 바다유어낚시어선 이용객의 경제적 손실평가연구 (Evaluating the Economic Damages to Anglers of the Marine Recreational Charter due to the Herbei Spirit Vessel Oil Spill)

  • 표희동
    • Ocean and Polar Research
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    • 제36권3호
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    • pp.289-302
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    • 2014
  • This paper aims to evaluate the indirect economic damages to anglers of the marine recreational charter caused by marine pollution associated with the Herbei Spirit vessel, which spilled 12,547 kl of crude oil in Taean coastal areas in December 2007. In order to evaluate the indirect cost to anglers of the charter fishing, consumer surplus for charter fishing is estimated using a Poisson model (PM), a negative binomial model (NBM), a truncated Poisson model (TPM), and a truncated negative binomial model (TNBM), which account for the characteristics of count data (non-negative discrete data), for individual travel cost method (ITCM). Because of over-dispersion problem in PM and TPM, NBM and TNBM are considered to be more appropriate statistically. All parameters such as income, fishing careers, travel cost and catch that are estimated are statistically significant and theoretically valid. Based on TNBM results, consumer surplus per trip and per person was estimated to be 277 thousand won, total consumer surplus per person and per year about 2.3 million won, and the marginal effect of consumer surplus on % changes in catch rate is about 33 thousand won. The consumer surplus was converted into total indirect economic damages for aggregation which are evaluated to be 125 billion won, reflecting the number of anglers and damage rate.

개별여행비용법을 이용한 바다 유어 낚시의 소비자 잉여추정 (Estimating Consumer Surplus for Recreational Sea Fishing using Individual Travel Cost Method)

  • 표희동;박철형;정진호
    • Ocean and Polar Research
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    • 제30권2호
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    • pp.141-148
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    • 2008
  • This paper aims at estimating consumer surplus for recreational sea fishing in Tongyeong coastal area using individual travel cost method. A Poisson model (PM), a negative binomial model (NBM), a truncated Poisson model (TPM), and a truncated negative binomial model (TNBM) are applied for individual travel cost method in order to account characteristics of count data (non-negative discrete data.) The survey was conducted for 462 inshore anglers using personal interview method in Tongyeong during July and October 2007. Respondents were asked about how often they do fishing, travel costs, catch, income, and so on. Because of over-dispersion problem in PM and TPM, NBM and TNBM were considered to be more appropriate statistically. All parameters estimated are statistically significant and theoretically valid. As the results based on TNBM, consumer surplus per trip was estimated to be 183,486 won, total consumer surplus per person and per year 3,399,658 won, and the marginal effect of consumer surplus on % changes in catch rate is 185,372 won.

Determinants of the Performance of Government Assistance to R&D Activities

  • Kwak, So-Yoon;Yoo, Seung-Hoon
    • Asian Journal of Innovation and Policy
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    • 제3권1호
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    • pp.94-116
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    • 2014
  • The technological innovation is considered as an important factor and there is a positive externality in developing technology in the form of technology spillover. In this context, it is argued that government should play an active role in advancing technology development and several means have been introduced. This study attempts to analyze manufacturing firms' evaluation for the performance of government assistance programs to their R&D activities. Considering that the performance evaluation takes the form of a count outcome, we apply several kinds of count data models. Some interesting findings emerge from the analysis. For example, we found that a firm's sales amount, dummy for the firm's having an R&D department, dummy for the firm's being a venture one, and the number of the firm's innovative activities have positive relationships with the degree that the firm evaluates government assistance as being useful.

A simple zero inflated bivariate negative binomial regression model with different dispersion parameters

  • Kim, Dongseok
    • Journal of the Korean Data and Information Science Society
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    • 제24권4호
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    • pp.895-900
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    • 2013
  • In this research, we propose a simple bivariate zero inflated negative binomial regression model with different dispersion for bivariate count data with excess zeros. An application to the demand for health services shows that the proposed model is better than existing models in terms of log-likelihood and AIC.

무선 랜 트래픽의 분석과 모델링 (Modeling and Analysis of Wireless Lan Traffic)

  • 대쉬도즈얌힌;이성진;원유집
    • 한국통신학회논문지
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    • 제33권8B호
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    • pp.667-680
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    • 2008
  • 본 논문에서는 802.11 무선 랜 네트워크 트래픽의 실제 관측 자료에 대한 연구 결과를 보인다. 패킷 트레이스는 대학 캠퍼스의 무선 랜 시설에서 얻은 자료로서 총합된 트래픽(aggregate traffic), 업스트림 트래픽(upstream traffic), 다운스트림 트래픽(downstream traffic), 그리고 TCP 패킷으로만 구성된 통합된 트래픽으로 이 4개의 트래픽 데이터를 수집하였다. 수집한 데이터에서 byte count 프로세스와 packet count 프로세스로 구성된 트래픽의 시계열과 시계열의 주변분포, 그리고 패킷 크기 분포에 대한 분석을 한다. 4개의 모든 데이터의 byte count 프로세스와 packet count 프로세스에서 장기 의존성 성질이 나타났다. 사용자가 인터넷으로 접속하는 없트�� 트래픽의 평균 패킷 크기는 151.7 byte였는데 다른 데이터의 평균 패킷 크기는 모드 260 byte 이상이었다. 최대 크기를 갖는 패이로드(payload)는 업스트림에서 3%, 그리고 나온트림에서 10%로 나타났다. 이런 분명한 패킷 크기 분포의 차이에도 불구하고 모든 4개의 데이터에서는 허스트(Hurst) 값이 모두 유사하게 나왔다. 허스트 값만으로는 트래픽의 확률적 특성을 충분히 설명할 수가 없다. 트래픽의 특성을 fractional-ARIMA(FARINA) 그리고 fractional Gaussian noise(FGN)으로 모델링을 한다. FGN은 연산을 하는데 있어서는 더 효율적이었고, FARINA는 트래픽 특성을 정확하게 모델링하는데 더 좋은 결과를 얻었다.

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

  • 백태헌;박민규;박병호
    • 한국도로학회논문집
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    • 제16권4호
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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.

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

  • 장학진;강윤회;이수범;김성욱
    • 응용통계연구
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    • 제21권4호
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    • pp.603-613
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    • 2008
  • 셀 수 있는 이산 자료 중에서 일반적인 모형에 비하여 영의 빈도가 과도하게 많이 관측되는 자료가 있다. 이러한 경우에 포아송 또는 음이항회귀모형과 같은 일반적인 회귀모형에 의한 분석은 적절하지 못하다. 본 논문에서는 영과잉 포아송회귀모형과 영과잉 음이항회귀모형에 대하여 베이지안 분석을 하였다. 또한, 마코브 연쇄 몬테카롤로 방법으로 계산한 베이즈 요인을 이용하여 모형선택을 하였다. 실제 교통사고 자료를 분석하여 이론적인 결과들을 뒷받침하였다.