• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.287-302
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• 1998

Saddlepoint approximation to the distribution function of sample mean(Daniels, 1987) is extended to the case of general statistic in this paper. The suggested approximation methods are applied to derive the approximations to the distributions of some statistics, including sample valiance and studentized mean. Some comparisons with other methods show that the suggested approximations are very accurate for moderate or small sample sizes. Even in extreme tail the accuracies are also maintained.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.27-34
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• 2023

The optimal assignment problem between agents and tasks is known as one of the representative problems of combinatorial optimization and an NP-hard problem. This paper covers multi agent-multi task assignment problems with uncertain completion probability. The completion probabilities are generally uncertain due to endogenous (agent or task) or exogenous factors in the system. Assignment decisions without considering uncertainty can be ineffective in a real situation that has volatility. To consider uncertain completion probability mathematically, a mathematical formulation with stochastic programming is illustrated. We also present an algorithm by using the sample average approximation method to solve the problem efficiently. The algorithm can obtain an assignment decision and the upper and lower bounds of the assignment problem. Through numerical experiments, we present the optimality gap and the variance of the gap to confirm the performances of the results. This shows the excellence and robustness of the assignment decisions obtained by the algorithm in the problem with uncertainty.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.917-922
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• 2018

In the conventional interchannel interference self-cancellation (ICI-SC) schemes, the length of sampling window is the same as the symbol length of orthogonal frequency division multiplexing (OFDM). Thus, the number of complex operations to compute the interference coefficient of each subchannel is significantly increased. To solve this problem, we present an approximated mathematical model for the coefficients of ICI-SC schemes. Based on the proposed approximation, we analyze mean squared error (MSE) and computational complexity of the ICI-SC schemes with the length of sampling window. As a result, the presented approximation has an error of less than 0.01% on the MSE compared to the original equation. When the number of subchannels is 1024, the number of complex computations for the interference coefficients is reduced by 98% or more. Since the computational complexity can be remarkably reduced without sacrificing the self-cancellation capability, it is considered that the proposed approximation is very useful to develop an algorithm for the ICI-SC scheme.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1309-1317
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• 2013

There are various parameter estimation methods for the generalized exponential distribution under progressive type I interval censoring. Chen and Lio (2010) studied the parameter estimation method by the maximum likelihood estimation method, mid-point approximation method, expectation maximization algorithm and methods of moments. Among those, mid-point approximation method has the smallest mean square error in the generalized exponential distribution under progressive type I interval censoring. However, this method is difficult to derive closed form of solution for the parameter estimation using by maximum likelihood estimation method. In this paper, we propose two type of approximate maximum likelihood estimate to solve that problem. The simulation results show the obtained estimators have good performance in the sense of the mean square error. And proposed method derive closed form of solution for the parameter estimation from the generalized exponential distribution under progressive type I interval censoring.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.809-818
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• 2014

Multivariate skew-normal distribution(distribution that includes multivariate normal distribution) has been recently applied to many application areas. We consider saddlepoint approximation for a statistic of linear combination based on a multivariate skew-normal distribution. This approach can be regarded as an extension of Na and Yu (2013) that dealt saddlepoint approximation for the distribution of a skew-normal sample mean for a linear statistic and multivariate version. Simulations results and examples with real data verify the accuracy and applicability of suggested approximations.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.57-66
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• 2005

In this paper, we propose a method to evaluate the solutions of the renewal equations related to SPRT for Erlang distribution. In SPRT, the Average Sample Number(ASN) and type I or type II error probabilities are shown in Fredholm type integral equations. The integral equations are generally solved by the approximation method using Gaussian quadrature. For Erlang distribution, it has been known that the exact solutions of the equations exist. We propose the algorithm to solve the equations.