• Title/Summary/Keyword: Poisson과정

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The Comparative Study for NHPP of Truncated Pareto Software Reliability Growth Model (절단고정시간에 근거한 파레토 NHPP 소프트웨어 신뢰성장모형에 관한 비교 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.12 no.1
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    • pp.9-16
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    • 2012
  • Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed for testing time. The testing time on the right is truncated in this model. The intensity function, mean-value function, reliability of the software, estimation of parameters and the special applications of Pareto NHPP model are discussed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection, depended on difference between predictions and actual values, were efficient using the mean square error and $R_{SQ}$.

Joint Modeling of Death Times and Counts Considering a Marginal Frailty Model (공변량을 포함한 사망시간과 치료횟수의 모형화를 위한 주변환경효과모형의 적용)

  • Park, Hee-Chang;Park, Jin-Pyo
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.311-322
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    • 1998
  • In this paper the problem of modeling count data where the observation period is determined by the survival time of the individual under study is considered. We assume marginal frailty model in the counts. We assume that the death times follow a Weibull distribution with a rate that depends on some covariates. For the counts, given a frailty, a Poisson process is assumed with the intensity depending on time and the covariates. A gamma model is assumed for the frailty. Maximum likelihood estimators of the model parameters are obtained. The model is applied to data set of patients with breast cancer who received a bone marrow transplant. A model for the time to death and the number of supportive transfusions a patient received is constructed and consequences of the model are examined.

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Effects of the Thermal Cracking on the Deformation Behaviour of Granites (열균열이 화강암의 변형거동에 미치는 영향)

    • Tunnel and Underground Space
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    • v.8 no.3
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    • pp.249-256
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    • 1998
  • Pocheon, Keochang and Sangju granite samples of different granularity and mineralogical composition were thermally treated at pre-determined temperature of $600^{\circ}C$. Thermally-induced microcracks were characterized using an optical microscopy and their effects on the deformation behavior of thermally cycled samples were studied performing compressive mechanical tests. Optical observations shows that by $600^{\circ}C$ nearlly all crystal boundaries open and the new intracrystalline cracks form in the more grains. The intracrystalline cracks are most pronounced at thermally treated Pocheon and Keochang granite samples. Results from mechanical tests represents negative lateral strains, which give negative Poisson's ratios. It is the most probable that negative lateral strains are produced by residual stresses induced during cooling.

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Ruin Probability on Insurance Risk Models (보험위험 확률모형에서의 파산확률)

  • Park, Hyun-Suk;Choi, Jeong-Kyu
    • The Korean Journal of Applied Statistics
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    • v.24 no.4
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    • pp.575-586
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    • 2011
  • In this paper, we study an asymptotic behavior of the finite-time ruin probability of the compound Poisson model in the case that the initial surplus is large. To compare an exact ruin probability with an approximate one, we place the focus on the exact calculation for the ruin probability when the claim size distribution is regularly varying tailed (i.e. exponential claims and inverse Gaussian claims). We estimate an adjustment coefficient in these examples and show the relationship between the adjustment coefficient and the safety premium. The illustration study shows that as the safety premium increases so does the adjustment coefficient. Larger safety premium means lower "long-term risk", which only stands to reason since higher safety premium means a faster rate of safety premium income to offset claims.

Jurisprudence in the History of Statistics (통계학사 속에서의 법)

  • Jo, Jae-Keun
    • Communications for Statistical Applications and Methods
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    • v.18 no.5
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    • pp.559-570
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    • 2011
  • The role of jurisprudence is examined in the early history of probability and statistics. From the mid-17th to the early 18th century, Christiaan Huygens and Jacob Bernoulli used mathematical expectation to solve the problems that originated from games of chance. We demonstrate that their concept of expectation as a fair price for participating in a game came from the legal concept of 'fair trade'. In addition, we consider that the probability that Bernoulli defined in his Ars Conjectandi originated from the legal concept of 'degree of certainty'. After considering some contributions of Laplace and Poisson, we examined the history of census and statistical survey in the early 19th century. Contrary to the history of the 17th and 18th century, statistics influenced society and law in the 19th century.

An Approach for the NHPP Software Reliability Model Using Erlang Distribution (어랑 분포를 이용한 NHPP 소프트웨어 신뢰성장 모형에 관한 연구)

  • Kim Hee-Cheul;Choi Yue-Soon;Park Jong-Goo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.1
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    • pp.7-14
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    • 2006
  • The finite failure NHPP models proposed in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, we propose the Erlang reliability model, which can capture the increasing nature of the failure occurrence rate per fault. Equations to estimate the parameters of the Erlang finite failure NHPP model based on failure data collected in the form of inter-failure times are developed. For the sake of proposing shape parameter of the Erlang distribution, we used to the goodness-of-fit test of distribution. Data set, where the underlying failure process could not be adequately described by the existing models, which motivated the development of the Erlang model. Analysis of the failure data set which led us to the Erlang model, using arithmetic and Laplace trend tests, goodness-of-fit test, bias tests is presented.

NHPP Software Reliability Model based on Generalized Gamma Distribution (일반화 감마 분포를 이용한 NHPP 소프트웨어 신뢰도 모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.6 s.38
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    • pp.27-36
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    • 2005
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates Per fault. This Paper Proposes reliability model using the generalized gamma distribution, which can capture the monotonic increasing(or monotonic decreasing) nature of the failure occurrence rate per fault. Equations to estimate the parameters of the generalized gamma finite failure NHPP model based on failure data collected in the form of interfailure times are developed. For the sake of proposing shape parameter of the generalized gamma distribution, used to the special pattern. Data set, where the underlying failure process could not be adequately described by the knowing models, which motivated the development of the gamma or Weibull model. Analysis of failure data set for the generalized gamma modell, using arithmetic and Laplace trend tests . goodness-of-fit test, bias tests is presented.

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The study for NHPP Software Reliability Model based on Kappa(2) distribution (Kappa(2) NHPP에 의한 소프트웨어 신뢰성 모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Computer Industry Society
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    • v.6 no.5
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    • pp.689-696
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    • 2005
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the Kappa(2) reliability model, which can capture the nomotonic decreasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on sum of the squared errors and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing two parameter of the Kappa distribution, was employed. This analysis of failure data compared with the Kappa model and the existing model using arithmetic and Laplace trend tests, bias tests is presented.

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A Parameter Estimation of Software Reliability Growth Model with Change-Point (변화점을 고려한 소프트웨어 신뢰도 성장모형의 모수추정)

  • Kim, Do-Hoon;Park, Chun-Gun;Nam, Kyung-H.
    • The Korean Journal of Applied Statistics
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    • v.21 no.5
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    • pp.813-823
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    • 2008
  • The non-homogeneous Poisson process(NHPP) based software reliability growth models are proved quite successful in practical software reliability engineering. The fault detection rate is usually assumed to be the continuous and monotonic function. However, the fault detection rate can be affected by many factors such as the testing strategy, running environment and resource allocation. This paper describes a parameter estimation of software reliability growth model with change-point problem. We obtain the maximum likelihood estimate(MLE) and least square estimate(LSE), and compare goodness-of-fit.

The Study for NHPP Software Reliability Growth Model based on Exponentiated Exponential Distribution (지수화 지수 분포에 의존한 NHPP 소프트웨어 신뢰성장 모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.5 s.43
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    • pp.9-18
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    • 2006
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

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