• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.79-83
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• 1997

This paper considers the problem of estimating the model parameters and reliability functions for Freund bivariate exponential distribution. Uniformly minimum variance unbiased estimators for model parameters, joint reliability and marginal reliability functions are obtained in the both case of non-identically distributed marginals and identically distributed marginals.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1213-1222
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• 2012

We shall derive the moment of the ratio Y/(X + Y) and the reliability P(X < Y ), and then observe the skewness of the ratio in a bivariate Pareto density function of (X, Y). And we shall consider an approximate MLE of parameters in the bivariate Pareto density function.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.949-954
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• 2009

The autoregressive process is applied in this paper to kernel regression in order to infer nonlinear models for predicting responses. We propose a kernel method for the autoregressive data which estimates the mean function by kernel machines. We also present the model selection method which employs the cross validation techniques for choosing the hyper-parameters which affect the performance of kernel regression. Artificial and real examples are provided to indicate the usefulness of the proposed method for the estimation of mean function in the presence of autocorrelation between data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.581-582
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• 2009

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1107-1117
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• 2005

We consider the problem of estimating the scale and shape parameters in the Weibull distribution based on censored samples. We propose the approximate maximum likelihood estimators (AMLEs) of the scale and shape parameters in the Weibull distribution based on Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error (MSE).

• Journal of the Korean Data and Information Science Society
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• v.3 no.1
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• pp.65-78
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• 1992

In this paper, we obtain the natural estimators of the coefficient parameters and propose strongly consistent estimators of the parameter in the autoregressive model of order three with non-negative innovations. It is shown that the natural estimators are also strongly consistent for the parameters. We also compare the proposed estimators with the natural estimators and the least square estimators via Monte Carlo simulation studies.

• Journal of applied mathematics & informatics
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• v.3 no.1
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• pp.55-64
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• 1996

Let $X_1, ....$X_P be p($\geq$2) independent random variables, where each X1 has a gamma distribution with $k_i and ${\heta}_i$. The problem is to simultaneously estimate p gammar parameters ${\heta}_i$ under entropy loss where the parameters are believed priori. Hierarchical bayes(HB) and empirical bayes(EB) estimators are investigated. Next computer simulation is studied to compute the risk percentage improvement of the HB, EB and the estimator of Dey et al.(1987) compared to MVUE of ${\heta}$.

• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.409-417
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• 2003

There are two rotation matrix parameters in a model, pro-posed by Prentice in 1989, for pairs of rotations in 3 dimensional space. For the least squares estimates of the two parameters, an algorithm was also presented, but it turned out that the algorithm could fail to get the least squares estimates. This article provides another algorithm for the least squares estimates and its performance is demonstrated by simulation results.

• Communications for Statistical Applications and Methods
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• v.3 no.1
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• pp.235-242
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• 1996

When the linear growth birth and death process observed at a set of equidistant time points, McNeil and Weiss (1997) present a method for simultaneously estimating the Malthusian parameter and the sum of the two parameters under wery restricted assumptions using a diffusion approximation. This article suggests a method, which does not require the restrictions given by Weiss, for estimating simultaneously the Malthusian parameter and the sum of the two parameters.

• Journal of Korean Society for Quality Management
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• v.13 no.1
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• pp.31-40
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• 1985

In this paper, statistical estimation of the parameters of the bivariate exponential distribution are studied. Bayes estimators of the parameters are obtained and compared with the maximum likelihood estimators which are introduced by Freund. We know that the method of moments estimators coincide with the maximum likelihood estimators and Bayes estimators are more efficient than the maximum likelihood estimators in moderate samples. The asymptotic distributions of the maximum likelihood estimators and the estimator of mean time to system failure are obtained.