• Journal of the Korean Statistical Society
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• v.32 no.1
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• pp.47-64
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• 2003

In this paper, we consider the asymptotic properties of asymmetric least squares estimators for nonlinear regression models. This paper provides sufficient conditions for strong consistency and asymptotic normality of the proposed estimators and derives asymptotic relative efficiency of the pro-posed estimators to the regression quantile estimators. We give some examples and results of a Monte Carlo simulation to compare the asymmetric least squares estimators with the regression quantile estimators.

• Journal of the Korean Statistical Society
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• v.15 no.2
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• pp.118-126
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• 1986

The relationships between combined estimators and generalized least squares estimators in block designs are reviewed. Here combined estimators mean the best linear combination of intrablock and interblock estimaters. It is well known that only for balanced incomplete block designs the combined estimators of Yates and of the generalized least squares estimators give the same result. In this paper, a general form of the combined estimators for treatment effects is derived and it can be seen that such estimators are equivalent to the generalized least squares estimators.

• 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.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.573-583
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• 2001

A condition in which the covariances of Matheron's variogram estimators are expressed in a simple form is reviewed. An asymptotic property of the covariances of the variogram estimators is examined, and a sufficient condition that guaranties the finiteness of the asymptotic variance of the normalized variogram estimators is provided.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.435-442
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• 2001

Bayes estimators and generalized ML estimators for reliability of a k-unit hot standby system with the perfect switch based upon a complete sample of failure times observed from an exponential distribution using noninformative, generalized uniform, and gamma priors for the failure rate are proposed, and MSE's of proposed several estimators for the standby system reliability are compared numerically each other through the Monte Carlo simulation.

• Journal of the Korean Statistical Society
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• v.34 no.2
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• pp.99-107
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• 2005

In this paper we consider the asymptotic mean squared error of positive part James-Stein estimators. In the normal-normal example, estimators of the mean squared error of these estimators are provided which are correct asymptotically up to O($m^{-l}$). Asymptotic estimators of the MSE's which correct up to O($m^{-l}$) are also provide. Here, m denotes the number of strata. A simulation study is undertaken to evaluate the performance of these estimators.

• 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.5 no.1
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• pp.213-222
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• 1998

In this paper we propose several estimators of Gini index of the two-parameter exponential distribution and obtain dis-tributions and moments of the proposed estimators. The proposed estimators are shown to cosistency and will be compares in terms of the proposed estimators. The proposed estimators are shown to cosistency and will be compared in terms of the mean squared error (MSE) through Monte Carlo method.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.837-843
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• 2000

Kreiss and Franke(192) and Allen and Datta(1999) proposed bootstrapping the M-estimators in ARMA models. In this paper, we introduce the robust estimating function and investigate the bootstrap approximations of the M-estimators which are solutions of the estimating equations in TAR models. A number of simulation results are presented to estimate the sampling distribution of the M-estimators, and asymptotic validity of the bootstrap for the M-estimators is established.

• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.323-337
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• 2004

This article coined a general class of estimators for various measures in normal population when some' a priori' or guessed value of standard deviation a is available in addition to sample information. The class of estimators is primarily defined for a function of standard deviation. An unbiased estimator and the minimum mean squared error estimator are worked out and the suggested class of estimators is compared with these classical estimators. Numerical computations in terms of percent relative efficiency and absolute relative bias established the merits of the proposed class of estimators especially for small samples. Simulation study confirms the excellence of the proposed class of estimators. The beauty of this article lies in estimation of various measures like standard deviation, variance, Fisher information, precision of sample mean, process capability index $C_{p}$, fourth moment about mean, mean deviation about mean etc. as particular cases of the proposed class of estimators.