• 제목/요약/키워드: log-logistic distribution

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로그-로지스틱 분포에 근거한 소프트웨어 고장 시간 절단 모형에 관한 비교연구 (The Comparative Study for Truncated Software Reliability Growth Model based on Log-Logistic Distribution)

  • 김희철;신현철
    • 융합보안논문지
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    • 제11권4호
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    • pp.85-91
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    • 2011
  • 소프트웨어 시스템의 대규모 응용 프로그램으로 인해, 소프트웨어 신뢰성은 소프트웨어 개발에서 중요한 역할올 담당하고 있다. 본 연구에서는 소프트웨어 신뢰성장 모형 중에서 고장 시간 절단 모형인 로그 로지스틱 분포에 근거한 모형이 제안되었다 고정시간에 따른 강도함수, 평균값함수, 신뢰도를 추정하였고 모수 추정은 최우 추정 법을 사용하였다. 실중분석에서는 이 분야에서 기본 모형인 포아송 실행 시간 모형과 비교 분석하였다. 그 결과 로그-로지스틱 모형이 기존의 로그 포아송 실행 시간 모형보다 신뢰성 측면에서 더 효율적이기 때문에 이 분야에서 기존 모형의 대안으로 로그-로지스틱모형을 사용할 수 있음을 확인 할 수 있었다.

반-로지스틱과 로그로지스틱 NHPP 분포 특성을 이용한 소프트웨어 최적방출시기 비교 연구 (The Comparative Study of Software Optimal Release Time of Finite NHPP Model Considering Half-Logistic and Log-logistic Distribution Property)

  • 김희철
    • 디지털산업정보학회논문지
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    • 제9권2호
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    • pp.1-10
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    • 2013
  • In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. In the course of correcting or modifying the software, finite failure non-homogeneous Poisson process model, presented and was proposed release policies of the life distribution, half-logistic and log-logistic distributions model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameter estimation using maximum likelihood estimation of failure time data make out, and software optimal release time was estimated.

Bayesian and maximum likelihood estimations from exponentiated log-logistic distribution based on progressive type-II censoring under balanced loss functions

  • Chung, Younshik;Oh, Yeongju
    • Communications for Statistical Applications and Methods
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    • 제28권5호
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    • pp.425-445
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    • 2021
  • A generalization of the log-logistic (LL) distribution called exponentiated log-logistic (ELL) distribution on lines of exponentiated Weibull distribution is considered. In this paper, based on progressive type-II censored samples, we have derived the maximum likelihood estimators and Bayes estimators for three parameters, the survival function and hazard function of the ELL distribution. Then, under the balanced squared error loss (BSEL) and the balanced linex loss (BLEL) functions, their corresponding Bayes estimators are obtained using Lindley's approximation (see Jung and Chung, 2018; Lindley, 1980), Tierney-Kadane approximation (see Tierney and Kadane, 1986) and Markov Chain Monte Carlo methods (see Hastings, 1970; Gelfand and Smith, 1990). Here, to check the convergence of MCMC chains, the Gelman and Rubin diagnostic (see Gelman and Rubin, 1992; Brooks and Gelman, 1997) was used. On the basis of their risks, the performances of their Bayes estimators are compared with maximum likelihood estimators in the simulation studies. In this paper, research supports the conclusion that ELL distribution is an efficient distribution to modeling data in the analysis of survival data. On top of that, Bayes estimators under various loss functions are useful for many estimation problems.

형상모수를 고려한 소프트웨어 신뢰성 비용 모형에 관한 비교 연구 (The Comparative Software Reliability Cost Model of Considering Shape Parameter)

  • 김경수;김희철
    • 디지털융복합연구
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    • 제12권3호
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    • pp.219-226
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    • 2014
  • 본 연구에서는 소프트웨어 제품 테스팅 과정에서 고장 수명분포의 형상모수를 고려한 소프트웨어 신뢰성 비용 모형에 대하여 연구 하였다. 신뢰성 분야에서 많이 사용되는 어랑 분포와 로그-로지스틱 모형을 이용한 형상모수를 반영한 문제를 제시하였다. 소프트웨어 고장모형은 유한고장 비동질적인 포아송과정을 이용하고 모수추정법은 최우추정법을 이용 하였다. 따라서 본 논문에서는 형상모수를 고려한 소프트웨어 비용모형 분석을 위하여 소프트웨어 고장 시간 자료를 적용하여 비교 분석하였다. 본 연구에서 사용된 어랑 분포와 로그-로지스틱분포에 근거한 소프트웨어 비용 모델을 비교한 결과 어랑 모형은 최적의 소프트웨어 방출 시간을 예측 할 수 있지만 로그-로지스틱 모형은 방출시간을 예측 할 수 없기 때문에 로그-로지스틱 보다 어랑 모형이 보다 효율적으로 나타나고 있다. 이 연구를 통하여 소프트웨어 개발자들은 소프트웨어 개발 비용을 파악 하는데 어느 정도 도움을 줄 수 있을 것으로 사료된다.

Bivariate odd-log-logistic-Weibull regression model for oral health-related quality of life

  • Cruz, Jose N. da;Ortega, Edwin M.M.;Cordeiro, Gauss M.;Suzuki, Adriano K.;Mialhe, Fabio L.
    • Communications for Statistical Applications and Methods
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    • 제24권3호
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    • pp.271-290
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    • 2017
  • We study a bivariate response regression model with arbitrary marginal distributions and joint distributions using Frank and Clayton's families of copulas. The proposed model is used for fitting dependent bivariate data with explanatory variables using the log-odd log-logistic Weibull distribution. We consider likelihood inferential procedures based on constrained parameters. For different parameter settings and sample sizes, various simulation studies are performed and compared to the performance of the bivariate odd-log-logistic-Weibull regression model. Sensitivity analysis methods (such as local and total influence) are investigated under three perturbation schemes. The methodology is illustrated in a study to assess changes on schoolchildren's oral health-related quality of life (OHRQoL) in a follow-up exam after three years and to evaluate the impact of caries incidence on the OHRQoL of adolescents.

Noninformative priors for the log-logistic distribution

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • 제25권1호
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    • pp.227-235
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    • 2014
  • In this paper, we develop the noninformative priors for the scale parameter and the shape parameter in the log-logistic distribution. We developed the first and second order matching priors. It turns out that the second order matching prior matches the alternative coverage probabilities, and is a highest posterior density matching prior. Also we revealed that the derived reference prior is the second order matching prior for both parameters, but Jerffrey's prior is not a second order matching prior. We showed that the proposed reference prior matches the target coverage probabilities in a frequentist sense through simulation study, and an example based on real data is given.

Bilevel-programming based failure-censored ramp-stress ALTSP for the log-logistic distribution with warranty cost

  • Srivastava, P.W.;Sharma, D.
    • International Journal of Reliability and Applications
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    • 제17권1호
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    • pp.85-105
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    • 2016
  • In this paper accelerated life testing is incorporated in quality control technique of acceptance sampling plan to induce early failures in high reliability products.Stress under accelerated condition can be applied in constant-stress, step-stress and progressive-stress or combination of such loadings. A ramp-stress results when stress is increased linearly (from zero) with time. In this paper optimum failure-censored ramp-stress accelerated life test sampling plan for log-logistic distribution has been formulated with cost considerations. The log-logistic distribution has been found appropriate for insulating materials. The optimal plans consist in finding optimum sample size, sample proportion allocated to each stress, and stress rate factor such that producer's and consumer's interests are safeguarded. Variance optimality criterion is used when expected cost per lot is not taken into consideration, and bilevel programming approach is used in cost optimization problems. The methods developed have been illustrated using some numerical examples, and sensitivity analyses carried out in the context of ramp-stress ALTSP based on variable SSP for proportion nonconforming.

Default Bayesian one sided testing for the shape parameter in the log-logistic distribution

  • Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • 제26권6호
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    • pp.1583-1592
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    • 2015
  • This paper deals with the problem of testing on the shape parameter in the log-logistic distribution. We propose default Bayesian testing procedures for the shape parameter under the reference priors. The reference prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. We can solve the this problem by the intrinsic Bayes factor and the fractional Bayes factor. Therefore we propose the default Bayesian testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

Applying Conventional and Saturated Generalized Gamma Distributions in Parametric Survival Analysis of Breast Cancer

  • Yavari, Parvin;Abadi, Alireza;Amanpour, Farzaneh;Bajdik, Chris
    • Asian Pacific Journal of Cancer Prevention
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    • 제13권5호
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    • pp.1829-1831
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    • 2012
  • Background: The generalized gamma distribution statistics constitute an extensive family that contains nearly all of the most commonly used distributions including the exponential, Weibull and log normal. A saturated version of the model allows covariates having effects through all the parameters of survival time distribution. Accelerated failure-time models assume that only one parameter of the distribution depends on the covariates. Methods: We fitted both the conventional GG model and the saturated form for each of its members including the Weibull and lognormal distribution; and compared them using likelihood ratios. To compare the selected parameter distribution with log logistic distribution which is a famous distribution in survival analysis that is not included in generalized gamma family, we used the Akaike information criterion (AIC; r=l(b)-2p). All models were fitted using data for 369 women age 50 years or more, diagnosed with stage IV breast cancer in BC during 1990-1999 and followed to 2010. Results: In both conventional and saturated parametric models, the lognormal was the best candidate among the GG family members; also, the lognormal fitted better than log-logistic distribution. By the conventional GG model, the variables "surgery", "radiotherapy", "hormone therapy", "erposneg" and interaction between "hormone therapy" and "erposneg" are significant. In the AFT model, we estimated the relative time for these variables. By the saturated GG model, similar significant variables are selected. Estimating the relative times in different percentiles of extended model illustrate the pattern in which the relative survival time change during the time. Conclusions: The advantage of using the generalized gamma distribution is that it facilitates estimating a model with improved fit over the standard Weibull or lognormal distributions. Alternatively, the generalized F family of distributions might be considered, of which the generalized gamma distribution is a member and also includes the commonly used log-logistic distribution.

지진 재현수준 예측에 대한 로그-로지스틱 분포와 일반화 극단값 분포의 비교 (Comparison of log-logistic and generalized extreme value distributions for predicted return level of earthquake)

  • 고낙경;하일도;장대흥
    • 응용통계연구
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    • 제33권1호
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    • pp.107-114
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    • 2020
  • 자연 재해로부터 관측되는 자료를 대상으로 재현 수준 예측 등과 같은 자료 분석을 위해 일반화 극단값 분포(generalized extreme value)가 자주 사용되어 왔다. 표본 수가 충분히 큰 경우 연속적인 블록 최댓값들은 점근적으로 일반화 극단값 분포를 따른다. 하지만 소표본인 경우 이러한 사실은 성립되지 않을 수도 있다. 본 논문에서는 이러한 문제점을 해결하기 위해 모형 적합도 검정 및 모형 선택을 통해 로그-로지스틱(log-logistic) 분포의 사용을 제안한다. 하나의 예증으로서 중국 지진 자료를 대상으로 하여 로그-로지스틱 분포를 이용하여 재현 기간별 재현 수준 예측 및 신뢰구간을 제시한다.