• Title/Summary/Keyword: 포아송 분포모형

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The Comparative Study of Software Optimal Release Time Based on Weibull Distribution Property (와이블 분포 특성에 근거한 소프트웨어 최적 방출시기에 관한 비교 연구)

  • Kim, Hee-Cheul;Park, Hyoung-Keun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.8
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    • pp.1903-1910
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    • 2009
  • In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used the Weibull distribution which has the efficient various property which has the place efficient quality. Thus, optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

Evaluation on the Reliability Attributes of Finite Failure NHPP Software Reliability Model Based on Pareto and Erlang Lifetime Distribution (파레토 및 어랑 수명분포에 근거한 유한고장 NHPP 소프트웨어 신뢰성모형의 신뢰도 속성에 관한 평가)

  • Min, Kyung-il
    • Journal of Industrial Convergence
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    • v.18 no.3
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    • pp.19-25
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    • 2020
  • In the software development process, software reliability evaluation is a very important issue. In particular, finding the optimal development model that satisfies high reliability is the more important task for software developers. For this, in this study, Pareto and Erlang life distributions were applied to the finite failure NHPP model to evaluate the reliability attributes. For this purpose, parametric estimation is applied to the maximum likelihood estimation method, and nonlinear equations are calculated using the bisection method. As a result, the Erlang model showed better performance than the Pareto model in the evaluation of the strength function and the mean value function. Also, as a result of inputting future mission time and evaluating reliability, the Erlang model showed an effectively high trend together with the Pareto model, while the Goel-Okumoto basic model showed a decreasing trend. In conclusion, the Erlang model is the best model among the proposed models. Through this study, it is expected that software developers will be able to use it as a basic guideline for exploring and evaluating the optimal software reliability model.

Mixed-effects zero-inflated Poisson regression for analyzing the spread of COVID-19 in Daejeon (혼합효과 영과잉 포아송 회귀모형을 이용한 대전광역시 코로나 발생 동향 분석)

  • Kim, Gwanghee;Lee, Eunjee
    • The Korean Journal of Applied Statistics
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    • v.34 no.3
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    • pp.375-388
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    • 2021
  • This paper aims to help prevent the spread of COVID-19 by analyzing confirmed cases of COVID-19 in Daejeon. A high volume of visitors, downtown areas, and psychological fatigue with prolonged social distancing were considered as risk factors associated with the spread of COVID-19. We considered the weekly confirmed cases in each administrative district as a response variable. Explanatory variables were the number of passengers getting off at a bus station in each administrative district and the elapsed time since the Korean government had imposed distancing in daily life. We employed a mixed-effects zero-inflated Poisson regression model because the number of cases was repeatedly measured with excess zero-count data. We conducted k-means clustering to identify three groups of administrative districts having different characteristics in terms of the number of bars, the population size, and the distance to the closest college. Considering that the number of confirmed cases might vary depending on districts' characteristics, the clustering information was incorporated as a categorical explanatory variable. We found that Covid-19 was more prevalent as population size increased and a district is downtown. As the number of passengers getting off at a downtown district increased, the confirmed cases significantly increased.

확률회귀모형을 이용한 고속도로의 사고요인 분석

  • Lee, Gi-Yeong;Lee, Yong-Taek
    • 도로교통
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    • s.94
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    • pp.51-64
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    • 2003
  • 본 연구는 사고요인과 사고모형의 문헌고찰을 통해 고속도로를 주행하는 버스와 화물차의 사고모형을 개발하고 그 적용방안에 대해 고찰하고자 수행되었다. 고속도로 사고 중 대형차로 인한 차량당 사고율은 승용차보다 월등히 높아 사고의 심각성을 나타내고 있으며, 따라서 이에 대한 별도의 검토가 필요한 시점에 와 있다. 특히 본 연구에 활용된 자료는 비집계된 사상자수로 구간자료를 집합화함으로써 발생하는 문제점을 해소할 수 있다. 모형의 분석기법으로 국내의 경우, 대부분 단순회귀식으로 사고모형을 개발, 적용하여 왔으나 사고수와 사상자수의 특성상 이산적 확률변수로 해석하여 포아송분포와 음이항분포로 적용하는 것이 바람직하다. 따라서 본 연구에서는 버스와 화물차의 사고유형별로 적합한 사고 모형을 개발하여 이로 인한 인사사고 요인에 대한 영향을 분석하고 그 적용방안을 제시하였다. 이러한 연구는 도로설계, 운영, 교통법규, 교통행정 등의 분야에서 거시적인 정책적 방향성을 제시하리라 판단된다. 특히 본 연구는 고속도로 운영주체인 한국도로공사의 고속도로사고조서를 바탕으로 사고유형별 사고모형을 개발, 적용한 것으로 고속도로의 안정성 향상을 위한 제반 정책 수립에 기초자료로 활용될 것으로 기대된다.

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Bayesian parameter estimation and prediction in NHPP software reliability growth model (NHPP소프트웨어 신뢰도 성장모형에서 베이지안 모수추정과 예측)

  • Chang, Inhong;Jung, Deokhwan;Lee, Seungwoo;Song, Kwangyoon
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.755-762
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    • 2013
  • In this paper we consider the NHPP software reliability model. And we deal with the maximum likelihood estimation and the Bayesian estimation with conjugate prior for parameter inference in the mean value function of Goel-Okumoto model (1979). The parameter estimates for the proposed model is presented by MLE and Bayes estimator in data set. We compare the predicted number of faults with the actual data set using the proposed mean value function.

A Software Reliability Cost Model Based on the Shape Parameter of Lomax Distribution (Lomax 분포의 형상모수에 근거한 소프트웨어 신뢰성 비용모형에 관한 연구)

  • Yang, Tae-Jin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.2
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    • pp.171-177
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    • 2016
  • Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this study, reliability software cost model considering shape parameter based on life distribution from the process of software product testing was studied. The cost comparison problem of the Lomax distribution reliability growth model that is widely used in the field of reliability presented. The software failure model was used the infinite failure non-homogeneous Poisson process model. The parameters estimation using maximum likelihood estimation was conducted. For analysis of software cost model considering shape parameter. In the process of change and large software fix this situation can scarcely avoid the occurrence of defects is reality. The conditions that meet the reliability requirements and to minimize the total cost of the optimal release time. Studies comparing emissions when analyzing the problem to help kurtosis So why Kappa efficient distribution, exponential distribution, etc. updated in terms of the case is considered as also worthwhile. In this research, software developers to identify software development cost some extent be able to help is considered.

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.

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.

Comparative Analysis on the Attributes of NHPP Software Development Cost Model Applying Gamma Family Distribution (감마족 분포을 적용한 NHPP 소프트웨어 개발비용 모형의 속성에 관한 비교 분석)

  • Hyo-Jeong Bae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.5
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    • pp.867-876
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    • 2023
  • In this study, the attributes of the NHPP software development cost model applying the Gamma family distribution (Erlang, Log-Logistic, Rayleigh) were newly analyzed, and after comparing with the Goel-Okumoto basic model to verify the properties of the model, the optimal model was also presented based on this. To analyze software reliability, failure time data that occurred randomly during system operation was used, and the calculation of the parameters was solved using the maximum likelihood estimation. As a result of comprehensive evaluation through various attribute analysis (mean value function, development cost, optimal release time), it was confirmed that the Rayleigh model had the best performance. Through this study, the attributes of the software development cost model applying the Gamma family distribution, which has no previous research case, were newly identified. Also, basic design data could also be presented so that developers can efficiently utilize this research data at an early stage.

A Bayesian Poisson model for analyzing adverse drug reaction in self-controlled case series studies (베이지안 포아송 모형을 적용한 자기-대조 환자군 연구에서의 약물상호작용 위험도 분석)

  • Lee, Eunchae;Hwang, Beom Seuk
    • The Korean Journal of Applied Statistics
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    • v.33 no.2
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    • pp.203-213
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    • 2020
  • The self-controlled case series (SCCS) study measures the relative risk of exposure to exposure period by setting the non-exposure period of the patient as the control period without a separate control group. This method minimizes the bias that occurs when selecting a control group and is often used to measure the risk of adverse events after taking a drug. This study used SCCS to examine the increased risk of side effects when two or more drugs are used in combination. A conditional Poisson model is assumed and analyzed for drug interaction between the narcotic analgesic, tramadol and multi-frequency combination drugs. Bayesian inference is used to solve the overfitting problem of MLE and the normal or Laplace prior distributions are used to measure the sensitivity of the prior distribution.