• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1409-1418
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• 2008

In this paper, we develop the reference priors for the common location parameter in two parameter exponential distributions. We derive the reference priors and prove the propriety of joint posterior distribution under the general prior including the reference priors. Through the simulation study, we show that the proposed reference prior matches the target coverage probabilities in a frequentist sense.

• Journal of the Korean Data and Information Science Society
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• 제16권1호
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• pp.107-114
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• 2005

We shall consider parametric estimations for the scale parameter in the exponential distribution when the parameter is function of a known exposure level, and obtain expectations and variances for their proposed estimators. And we shall compare numerically efficiencies for proposed estimators of the scale parameter in the small sample sizes.

• International Journal of Reliability and Applications
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• 제14권2호
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• pp.79-96
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• 2013

Exponential distribution plays a key role in engineering reliability and its applications. The exponential failure model has been studied for years. This article introduces two new preliminary test estimators for the reliability function (R(t)) in complete and censored samples from the exponential model with the use of a prior estimation (${\theta}_0$) of the mean (${\theta}$). The proposed preliminary test estimators are studied and compared numerically with the existing estimators. Computer-intensive calculations for bias and relative efficiency show that for, different values of levels of significance and for varying constants involved in the proposed estimators, the proposed estimators are far better than classical and existing estimators.

• Journal of Information Technology Applications and Management
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• 제27권3호
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• pp.69-75
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• 2020

In this paper, we applied the shape parameters of the exponentialized exponential life distribution widely used in the field of software reliability, and compared the reliability properties of the software using the non-homogeneous Poisson process in finite failure. In addition, the average value function is also a non-decreasing form. In the case of the larger the shape parameter, the smaller the estimated error in predicting the predicted value in comparison with the true value, so it can be regarded as an efficient model in terms of relative accuracy. Also, in the larger the shape parameter, the larger the estimated value of the coefficient of determination, which can be regarded as an efficient model in terms of suitability. So. the larger the shape parameter model can be regarded as an efficient model in terms of goodness-of-fit. In the form of the reliability function, it gradually appears as a non-increasing pattern and the higher the shape parameter, the lower it is as the mission time elapses. Through this study, software operators can use the pattern of mean square error, mean value, and hazard function as a basic guideline for exploring software failures.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.899-910
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• 2004

In this paper we have proposed a new loss function, namely, non-linear exponential(NLINEX) loss function, which is quite asymmetric in nature. We obtained the Bayes estimator under exponential(LINEX) and squared error(SE) loss functions. Moreover, a numerical comparison among the Bayes estimators of power function distribution under SE, LINEX, and NLINEX loss function have been made.

• Journal of the Korean Data and Information Science Society
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• 제14권4호
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• pp.983-988
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• 2003

When the available sample is multiply Type-II censored, the maximum likelihood estimators of the location and the scale parameters of two-parameter exponential distribution do not admit explicitly. In this case, we propose some approximate maximum likelihood estimators by approximating the likelihood equations appropriately. We present an example to illustrate these estimation methods.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1999년도 춘계학술대회 논문집
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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.

• International Journal of Reliability and Applications
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• 제15권2호
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• pp.111-123
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• 2014

A new class of bivariate distributions is derived by specifying its conditionals as the exponential and gamma distributions. Some properties and relations with other distributions of the new class are studied. In particular, the estimation of parameters is considered by the methods of maximum likelihood and pseudolikelihood of a special case of the new class. An application using a real bivariate data is given for illustrating the flexibility of the new class in this context, and, also, for comparing the estimation results obtained by the maximum likelihood and pseudolikelihood methods.

• Journal of the Korean Data and Information Science Society
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• 제26권6호
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• pp.1573-1582
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• 2015

In lifetime data analysis, it is generally known that the lifetimes of test items may not be recorded exactly. There are also situations wherein the withdrawal of items prior to failure is prearranged in order to decrease the time or cost associated with experience. Moreover, it is generally known that more than one cause or risk factor may be present at the same time. Therefore, analysis of censored competing risks data are needed. In this article, we derive the Bayes estimators for the entropy function under the exponential distribution with an unknown scale parameter based on multiply Type II censored competing risks data. The Bayes estimators of entropy function for the exponential distribution with multiply Type II censored competing risks data under the squared error loss function (SELF), precautionary loss function (PLF) and DeGroot loss function (DLF) are provided. Lindley's approximate method is used to compute these estimators.We compare the proposed Bayes estimators in the sense of the mean squared error (MSE) for various multiply Type II censored competing risks data. Finally, a real data set has been analyzed for illustrative purposes.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• 제3권3호
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• pp.149-153
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• 2022

The degree distribution of the plant-pollinator network was identified by analyzing the data in the ecosystem and reproduced by a model of the growing bipartite mutualistic networks. The degree distribution of pollinator shows power law or stretched exponential distribution, while plant usually shows stretched exponential distribution. In the growth model, the plant and the pollinator are selected with probability P_p and P_A=1-P_p, respectively. The number of incoming links for the plant and the pollinator is l_p and l_A, respectively. The probability that the link of the plant selects the pollinator of the existing network given as $A_{k_i}=k^{{\lambda}_A}_i/{\sum}_i\;k^{{\lambda}_A}_i$, and the probability that the pollinator selects the plant is $P_{k_i}=k^{{\lambda}_p}_i/{\sum}_i\;k^{{\lambda}_p}_i$. When the nonlinear growth index is 𝛌_X=1 (X=A or P), the degree distribution follows a power law, and if 0≤𝛌_X<1, the degree distribution follows a stretched exponential distribution. The cumulative degree distributions of plants and pollinators of 14 empirical plant-pollinators included in Interaction Web Database were calculated. A set of parameters (P_A,P_P,l_A,l_P) that reproduces these cumulative degree distributions and a growth index 𝛌_X (X=A or P) were obtained. We found that animal takes very heterogenous connections, whereas plant takes a more flexible connection network.