• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.863-875
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• 2010

In this paper we apply the martingale approach, which has been widely used in mathematical finance, to investigate the optimal investment problem for an insurer under the criterion of mean-variance. When the risk and security assets are described by the L$\acute{e}$vy processes, the closed form solutions to the maximization problem are obtained. The mean-variance efficient strategies and frontier are also given.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.178-181
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• 2003

In this paper, it proposes the efficient iterative decoding stop criterion using the variance value of LLR. It is verifying that the proposal iterative decoding stop criterion can be reduced the average iterative decoding number compared to conventional schemes with a negligible degradation of the error performance.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.29-37
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• 2001

In this paper, we consider the second order probability matching criterion for the ratio of the variance components under the one-way random effect model. It turns out that among all of the reference priors given in Ye(1994), the only one reference prior satisfies the second order matching criterion. Similar results are also obtained for the intraclass correlation as well.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.317-328
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• 2002

We first derive group ordering reference priors in a two-way mixed-effects analysis of variance (ANOVA) model. We show that posterior distributions are proper and provide marginal posterior distributions under reference priors. We also examine whether the reference priors satisfy the probability matching criterion. Finally, the reference prior satisfying the probability matching criterion is shown to be good in the sense of frequentist coverage probability of the posterior quantile.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.559-568
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• 2006

In this paper, we develop the noninformative priors for the linear mixed models when the parameter of interest is the ratio of variance components. We developed the first and second order matching priors. We reveal that the one-at-a-time reference prior satisfies the second order matching criterion. It turns out that the two group reference prior satisfies a first order matching criterion, but Jeffreys' prior is not first order matching prior. Some simulation study is performed.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.485-501
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• 2012

This research is to find a design D that minimizes forecast variance in d dimensions over the candidate space ${\chi}$. We want a robust design since we may not know the specific covariance structure. We seek a design that minimizes a coverage criterion and hope that this design will provide a small forecast variance even if the covariance structure is unobservable. The details of an exchange or swapping algorithm and several properties of the parameters of coverage criterion with the unknown correlation structures are discussed.

• Journal of Korean Society for Quality Management
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• v.11 no.1
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• pp.24-29
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• 1983

A criterion is developed from the integrated sum of weighted squared bias and variance for use in selecting regressors. Some properties of this criterion are discussed and an example illustrating its use is included.

• International Journal of Quality Innovation
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• v.1 no.1
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• pp.32-37
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• 2000

In an industrial process, the proper objective is to find the optimal operating conditions with minimum process variability around the target. Vining and Myers(1990) suggest to use the separate model for the mean response and the process varian linear predictor ${\tau}_i={\log}\;{\sigma}^2_i$ is unknown and should be estimated. Noting that the variance of $\hat{{\tau}_i}$ is heterogeneous, another appropriate D-optimality criterion $D_3$ based on the method of generalized least squares is proposed in this paper.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.28-31
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• 2003

In this paper, it proposes the efficient iterative decoding stop criterion using the variance value of LLR. It is verifying that the proposal iterative de-coding stop criterion can be reduced the average iterative decoding number. The proposal algorithm md hardware synthesize to use the Synopsys Tool, performance validations perform through the ModelSim.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.103-110
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• 2006

Turbo code, a kind of error correction coding technique, has been used in the field of digital mobile communication system. As the number of iterations increases, it can achieves remarkable BER performance over AWGN channel environment. However, if the number of iterations Is increases in the several channel environments, any further iteration results in very little improvement, and requires much delay and computation in proportion to the number of iterations. To solve this problems, it is necessary to device an efficient criterion to stop the iteration process and prevent unnecessary delay and computation. In this paper, it proposes an efficient and simple criterion for stopping the iteration process in turbo decoding. By using variance values of noise derived from mean values of LLR in turbo decoder, the proposed algorithm can largely reduce the computation and average number of iterations without BER performance degradation. As a result of simulations, the computation of the proposed algorithm is reduced by about $66{\sim}80%$ compared to conventional algorithm. The average number of iterations is reduced by about $13.99%{\sim}15.74%$ compared to CE algorithm and about $17.88%{\sim}18.59%$ compared to SCR algorithm.