• Title/Summary/Keyword: exponential analysis

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Bayesian Multiple Comparisons for K-Exponential Populations with Type-II Censored Data by Fractional Bayes Factors

  • Mun, Gyeong-Ae;Kim, Dal-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.1
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    • pp.67-77
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    • 2002
  • We propose the Bayesian testing for the equality of K-exponential populations means with Type-II censored data. Specially we use the fractional Bayesian factors suggested by O'Hagan (1995) based on the noninformative priors for the parameters. And, we investigate the usefulness of the proposed Bayesian testing procedures via both real data analysis and simulations and compare the classical likelihood ratio(LR) test with the proposed Bayesian test.

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Stochastic Inventory Model with an Exponential Decay (지수적 변질과정의 재고시스템에 관한 연구)

  • 김영민
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.9 no.13
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    • pp.39-43
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    • 1986
  • This thesis aims to find an optimal inventory of probabilistic model with an exponential decay. This system is divided into the production period and non-production period and the behavior of each period is analyzed by birth and death process. The result of this analysis gives how to decide the economic production quantity and the optimal production cycle.

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STABILITY OF IMPULSIVE CELLULAR NEURAL NETWORKS WITH TIME-VARYING DELAYS

  • Zhang, Lijuan;Yu, Lixin
    • Journal of applied mathematics & informatics
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    • v.29 no.5_6
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    • pp.1327-1335
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    • 2011
  • This paper demonstrates that there is a unique exponentially stable equilibrium state of a class of impulsive cellular neural network with delays. The analysis exploits M-matrix theory and generalized comparison principle to derive some easily verifiable sufficient conditions for the global exponential stability of the equilibrium state. The results extend and improve earlier publications. An example with its simulation is given for illustration of theoretical results.

Estimation of Parameters in a Generalized Exponential Semi-Markov Reliability Models

  • El-Gohary Awad
    • International Journal of Reliability and Applications
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    • v.6 no.1
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    • pp.13-29
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    • 2005
  • This paper deals with the stochastic analysis of a three-states semi-Markov reliability model. Using both the maximum likelihood and Bayes procedures, the parameters included in this model are estimated. Next, assuming that the lifetime and repair time are generalized exponential random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is discussed. Finally, some of the obtained results are compared with those available in the literature.

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GLOBAL EXPONENTIAL STABILITY OF BAM NEURAL NETWORKS WITH IMPULSES AND DISTRIBUTED DELAYS

  • Shao, Yuanfu;Luo, Zhenguo
    • Journal of applied mathematics & informatics
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    • v.29 no.1_2
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    • pp.103-117
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    • 2011
  • By using an important lemma, some analysis techniques and Lyapunov functional method, we establish the sufficient conditions of the existence of equilibrium solution of a class of BAM neural network with impulses and distributed delays. Finally, applications and an example are given to illustrate the effectiveness of the main results.

Effects of Cell Residence Time Distributions in Cellular Mobile Communication Systems

  • Yeo, Kun-Min;Jun, Chi-Hyuck
    • Proceedings of the Korea Society for Simulation Conference
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    • 1999.04a
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    • pp.6-10
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    • 1999
  • We present a simulation result to the analysis of the effects of cell residence time distributions upon the expected channel occupancy time based on an analytic mobility model. Numerical examples show that exponential distribution provides upper and lower bound to the expected channel occupancy times of new calls and handoff calls. This fact reveals that the assumption of exponential distribution as the cell residence time distribution as the cell residence time distribution may over- or under-estimate cellular mobile systems.

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Bayes Computations for the Reliability in a Bivariate Exponential Model

  • In Suk Lee;Jang Sik Cho;Sang Gil Kang;Jeong Hwan Ko
    • Communications for Statistical Applications and Methods
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    • v.5 no.1
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    • pp.145-153
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    • 1998
  • In this paper, a hierarchical Bayesian analysis of a bivariate exponential model is discussed using Gibbs sampler. Parameters and reliability estimators are obtained. A numerical study is provided.

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Bayesian Analysis for the Difference of Exponential Means

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.04a
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    • pp.135-144
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    • 2005
  • In this paper, we develop the noninformative priors for the exponential models when the parameter of interest is the difference of two means. We develop the first and second order matching priors. We reveal that the second order matching priors do not exist. It turns out that Jeffreys' prior does not satisfy a first order matching criterion. The Bayesian credible intervals based on the first order matching meet the frequentist target coverage probabilities much better than the frequentist intervals of Jeffreys' prior.

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Lifetime estimation of Plasma Display Panel

  • Chung, Kyeong-Woon;Kim, Young-Kwan;Kurai, Teruo;Kim, Hyun-Tak
    • 한국정보디스플레이학회:학술대회논문집
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    • 2008.10a
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    • pp.161-164
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    • 2008
  • We proposed 2-phase regression of power function inside exponential for PDP lifetime data analysis. In introducing our method we discussed the reason why PDP degradation behavior is described by exponential function basically. By applying our method to 50HD and 50FHD PDP lifetime experiment data, we obtained more than 100,000Hr lifetime. From these results, we claim that PDP lifetime is more than 100,000Hr.

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Bayesian multiple comparisons in Freund's bivariate exponential populations with type I censored data

  • Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.3
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    • pp.569-574
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    • 2010
  • We consider two components system which have Freund's bivariate exponential model. In this case, Bayesian multiple comparisons procedure for failure rates is sug-gested in K Freund's bivariate exponential populations. Here we assume that the com-ponents enter the study at random over time and the analysis is carried out at some prespeci ed time. We derive fractional Bayes factor for all comparisons under non- informative priors for the parameters and calculate the posterior probabilities for all hypotheses. And we select a hypotheses which has the highest posterior probability as best model. Finally, we give a numerical examples to illustrate our procedure.