• Title/Summary/Keyword: Exponential Random Variable

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Accelerated Life Tests under Gamma Stress Distribution (스트레스함수가 감마분포인 가속수명시험)

  • 원영철
    • Journal of the Korea Safety Management & Science
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    • v.4 no.3
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    • pp.59-66
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    • 2002
  • This paper presents accelerated life tests for Type I censoring data under probabilistic stresses. Probabilistic stress, S, is the random variable for stress influenced by test environments, test equipments, sampling devices and use conditions. The hazard rate, $\theta$ is a random variable of environments and a function of probabilistic stress. In detail, it is assumed that the hazard rate is linear function of the stress, the general stress distribution is a gamma distribution and the life distribution for the given hazard rate, $\theta$is an exponential distribution. Maximum likelihood estimators of model parameters are obtained, and the mean life in use stress condition is estimated. A hypothetical example is given to show its applicability.

An One-for-One Ordering Inventory Policy with Poisson Demands and Losses with Order Dependent Leadtimes

  • Choi, Jin-Yeong;Kim, Man-Sik
    • Journal of the Korean Operations Research and Management Science Society
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    • v.12 no.1
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    • pp.27-33
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    • 1987
  • A stochastic model for an inventory system in which depletion of stock takes place due to random demand as well as random loss of items is studied under the assumption that the intervals between cussessive unit demands as well as those between cussessive unit losses, are independently and identically distributed random variables having negative exponential distributions with respective parameters .mu. and .lambda. It is further assumed that leadtime for each order is an outstanding-order-dependent random variable. The steady state probability distribution of the net inventory level is derived under the continuous review (S -1, S) inventory policy, from which the total expected coast expression is formulated.

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ON ALMOST SURE CONVERGENCE FOR WEIGHTED SUMS OF LNQD RANDOM VARIABLES

  • Choi, Jeong-Yeol;Kim, So-Youn;Baek, Jong-Il
    • Honam Mathematical Journal
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    • v.34 no.2
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    • pp.241-252
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    • 2012
  • Let $\{X_{ni},\;1{\leq}i{\leq}n,\;n{\geq}1\}$ be a sequence of LNQD which are dominated randomly by another random variable X. We obtain the complete convergence and almost sure convergence of weighted sums ${\sum}^n_{i=1}a_{ni}X_{ni}$ for LNQD by using a new exponential inequality, where $\{a_{ni},\;1{\leq}i{\leq}n,\;n{\geq}1\}$ is an array of constants. As corollary, the results of some authors are extended from i.i.d. case to not necessarily identically LNQD case.

Optimal Plan of Partially Accelerated Life Tests under Type I Censoring

  • Moon, Gyoung-Ae
    • Journal of the Korean Data and Information Science Society
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    • v.5 no.2
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    • pp.87-94
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    • 1994
  • In this paper, we consider optimum plan to determine stress change times under the three-step stress PALTs, assuming that each test units follows an exponential distribution. The tampered random variable(TRV) model for the three-step stress PALTs setup are introduced, and maximum likelihood estimators(MLEs) of the failure rate and the acceleration factors are obtained. The change times to minimize the generalized asymptotic variance(GAVR) of MLEs of the failure rate and the acceleration factors are proposed for the three-step stress PALTs.

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Determining an Optimal Production Time for EPQ Model with Preventive Maintenance and Defective Rate (생산설비의 유지보수서비스와 제품의 불량률을 고려한 최적 생산주기 연구)

  • Kim, Migyoung;Park, Minjae
    • Journal of Korean Society for Quality Management
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    • v.47 no.1
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    • pp.87-96
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    • 2019
  • Purpose: The purpose of this paper is to determine an optimal production time for economic production quantity model with preventive maintenance and random defective rate as the function of a machinery deteriorates. Methods: If a machinery shifts from "in-control" state to "out-of-control" state, a proportion of defective items being produced increases. It is assumed that time to state shift is a random variable and follows an arbitrary distribution. The elapsed time until process shift decreases stochastically as a production cycle repeats and quasi-renewal process is used to implement for production facilities to deteriorate. Results: When the exponential parameter for exponential distribution increases, the optimal production time increases. When Weibull distribution is considered, the optimal production time is closely affected by the shape parameter of Weibull distribution. Conclusion: A mathematical model is suggested to find optimal production time and optimal number of production cycles and numerical examples are implemented to validate the patterns for changes of optimal times under different parameters assumptions. The real application is implemented using the proposed approach.

NUMERICAL SOLUTION OF STOCHASTIC DIFFERENTIAL EQUATION CORRESPONDING TO CONTINUOUS DISTRIBUTIONS

  • Amini, Mohammad;Soheili, Ali Reza;Allahdadi, Mahdi
    • Communications of the Korean Mathematical Society
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    • v.26 no.4
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    • pp.709-720
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    • 2011
  • We obtain special type of differential equations which their solution are random variable with known continuous density function. Stochastic differential equations (SDE) of continuous distributions are determined by the Fokker-Planck theorem. We approximate solution of differential equation with numerical methods such as: the Euler-Maruyama and ten stages explicit Runge-Kutta method, and analysis error prediction statistically. Numerical results, show the performance of the Rung-Kutta method with respect to the Euler-Maruyama. The exponential two parameters, exponential, normal, uniform, beta, gamma and Parreto distributions are considered in this paper.

Effects on Regression Estimates under Misspecified Generalized Linear Mixed Models for Counts Data

  • Jeong, Kwang Mo
    • The Korean Journal of Applied Statistics
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    • v.25 no.6
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    • pp.1037-1047
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    • 2012
  • The generalized linear mixed model(GLMM) is widely used in fitting categorical responses of clustered data. In the numerical approximation of likelihood function the normality is assumed for the random effects distribution; subsequently, the commercial statistical packages also routinely fit GLMM under this normality assumption. We may also encounter departures from the distributional assumption on the response variable. It would be interesting to investigate the impact on the estimates of parameters under misspecification of distributions; however, there has been limited researche on these topics. We study the sensitivity or robustness of the maximum likelihood estimators(MLEs) of GLMM for counts data when the true underlying distribution is normal, gamma, exponential, and a mixture of two normal distributions. We also consider the effects on the MLEs when we fit Poisson-normal GLMM whereas the outcomes are generated from the negative binomial distribution with overdispersion. Through a small scale Monte Carlo study we check the empirical coverage probabilities of parameters and biases of MLEs of GLMM.

Other approaches to bivariate ranked set sampling

  • Al-Saleh, Mohammad Fraiwan;Alshboul, Hadeel Mohammad
    • Communications for Statistical Applications and Methods
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    • v.25 no.3
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    • pp.283-296
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    • 2018
  • Ranked set sampling, as introduced by McIntyre (Australian Journal of Agriculture Research, 3, 385-390, 1952), dealt with the estimation of the mean of one population. To deal with two or more variables, different forms of bivariate and multivariate ranked set sampling were suggested. For a technique to be useful, it should be easy to implement in practice. Bivariate ranked set sampling, as introduced by Al-Saleh and Zheng (Australian & New Zealand Journal of Statistics, 44, 221-232, 2002), is not easy to implement in practice, because it requires the judgment ranking of each of the combination of the order statistics of the two characteristics. This paper investigates two modifications that make the method easier to use. The first modification is based on ranking one variable and noting the rank of the other variable for one cycle, and do the reverse for another cycle. The second approach is based on ranking of one variable and giving the second variable the same rank (Concomitant Order Statistic) for one cycle and do the reverse for the other cycle. The two procedures are investigated for an estimation of the means of some well-known distributions. It is show that the suggested approaches can be used in practice and can be more efficient than using SRS. A real data set is used to illustrate the procedure.

Prevention of suspension bridge flutter using multiple tuned mass dampers

  • Ubertini, Filippo
    • Wind and Structures
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    • v.13 no.3
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    • pp.235-256
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    • 2010
  • The aeroelastic stability of bridge decks equipped with multiple tuned mass dampers is studied. The problem is attacked in the time domain, by representing self-excited loads with the aid of aerodynamic indicial functions approximated by truncated series of exponential filters. This approach allows to reduce the aeroelastic stability analysis in the form of a direct eigenvalue problem, by introducing an additional state variable for each exponential term adopted in the approximation of indicial functions. A general probabilistic framework for the optimal robust design of multiple tuned mass dampers is proposed, in which all possible sources of uncertainties can be accounted for. For the purposes of this study, the method is also simplified in a form which requires a lower computational effort and it is then applied to a general case study in order to analyze the control effectiveness of regular and irregular multiple tuned mass dampers. A special care is devoted to mistuning effects caused by random variations of the target frequency. Regular multiple tuned mass dampers are seen to improve both control effectiveness and robustness with respect to single tuned mass dampers. However, those devices exhibit an asymmetric behavior with respect to frequency mistuning, which may weaken their feasibility for technical applications. In order to overcome this drawback, an irregular multiple tuned mass damper is conceived which is based on unequal mass distribution. The optimal design of this device is finally pursued via a full domain search, which evidences a remarkable robustness against frequency mistuning, in the sense of the simplified design approach.

Analytical Approximation Algorithm for the Inverse of the Power of the Incomplete Gamma Function Based on Extreme Value Theory

  • Wu, Shanshan;Hu, Guobing;Yang, Li;Gu, Bin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.12
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    • pp.4567-4583
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    • 2021
  • This study proposes an analytical approximation algorithm based on extreme value theory (EVT) for the inverse of the power of the incomplete Gamma function. First, the Gumbel function is used to approximate the power of the incomplete Gamma function, and the corresponding inverse problem is transformed into the inversion of an exponential function. Then, using the tail equivalence theorem, the normalized coefficient of the general Weibull distribution function is employed to replace the normalized coefficient of the random variable following a Gamma distribution, and the approximate closed form solution is obtained. The effects of equation parameters on the algorithm performance are evaluated through simulation analysis under various conditions, and the performance of this algorithm is compared to those of the Newton iterative algorithm and other existing approximate analytical algorithms. The proposed algorithm exhibits good approximation performance under appropriate parameter settings. Finally, the performance of this method is evaluated by calculating the thresholds of space-time block coding and space-frequency block coding pattern recognition in multiple-input and multiple-output orthogonal frequency division multiplexing. The analytical approximation method can be applied to other related situations involving the maximum statistics of independent and identically distributed random variables following Gamma distributions.