• Communications for Statistical Applications and Methods
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• 제6권1호
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• pp.1-10
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• 1999

When the component proportions in mixture experiments are restricted by lower and upper bounds multicollinearity appears all too frequently. The ridge regression can be used to stabilize the coefficient estimates in the fitted model. I propose a graphical method for evaluating the mixture component effects of ridge regression estimator with respect to the prediction variance and the prediction bias.

• The Korean Journal of Applied Statistics
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• 제20권2호
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• pp.281-290
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• 2007

Linear estimator, a weighted sum of the sample observation, is commonly adopted to estimate the finite population parameters such as population totals in survey sampling. The weight for a sampled unit is often constructed by multiplying the base weight, which is the inverse of the first-order inclusion probability, by an adjustment term that takes into account of the auxiliary information obtained throughout the population. The linear estimator using the weight adjustment is often more efficient than the one using only the bare weight, but its valiance estimation is more complicated. We discuss variance estimation for a general class of weight-adjusted estimator. By identifying that the weight-adjusted estimator can be viewed as a function of estimated nuisance parameters, where the nuisance parameters were used to incorporate the auxiliary information, we derive a linearization of the weight-adjusted estimator using a Taylor expansion. The method proposed here is quite general and can be applied to wide class of the weight-adjusted estimators. Some examples and results from a simulation study are presented.

• Communications for Statistical Applications and Methods
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• 제6권1호
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• pp.285-292
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• 1999

In this paper we propose the several estimators of the Lorenz curve in the Pareto distribution and obtain the bias and the mean squared error for each estimator. We compare the proposed estimators with the uniformly minimum variance unbiased estimator (UMVUE) and the maximum likelihood estimator (MLE) in terms of the mean squared error (MSE) through Monte Carlo methods and discuss the results.

• Journal of the Korean Data and Information Science Society
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• 제6권2호
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• pp.1-7
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• 1995

This paper considers the reliability estimation of a two-component shared-load system based on Freund model. Maximum likelihood estimator, order restricted maximum likelihood estimator and uniformly minimum variance unbiased estimator of the reliability function for the system are obtained. Performance of three estimators for moderate sample sizes is studied by simulation.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.257-269
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• 2001

The simulation is used to estimate an overflow probability in a stable parallel network with coupled inputs. Since the general simulation needs extremely many trials to obtain such a small probability, the fast simulation is proposed to reduce trials instead. By using the Cramer’s theorem, we first obtain an optimally changed measure under which the variance of the estimator is minimized. Then, we use it to derive an importance sampling estimator of the overflow probability which enables us to perform the fast simulation.

• Journal of the Korean Statistical Society
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• 제30권4호
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• pp.637-644
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• 2001

We investigated two kinds of mean square error (MSE) estimator of homogeneous linear estimator (HLE) for the population total under stratified multi-stage sampling. One is studied when the second stage variance component is estimable and the other is found in cafe it is not estimable. The proposed estimators are necessary forms of non-negative unbiased MSE estimators of HLE.

• Journal of the Korean Statistical Society
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• 제16권1호
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• pp.21-25
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• 1987

The combined estimator of inter- and intra-block estimators in incomplete block designs can be expressed as a weighted average of two location estimators. The weight should be between 0 and 1. However, the negative variance component estimate could result in the weight being negative or larger than 1. In this paper, we show that if two location estimators have symmetric unimodal distributions, truncating the weight to 0 or 1 accordingly improves the combined estimator under an arbitrary convex loss function.

• Journal of the Korean Statistical Society
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• 제34권4호
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• pp.345-366
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• 2005

This paper considers the cointegrating vector estimator in the error correction model with stationary covariates, which combines the stationary vector autoregressive model and the nonstationary error correction model. The cointegrating vector estimator is shown to follow the locally asymptotically mixed normal distribution. The variance of the estimator depends on the co­variate effect of stationary regressors, and the asymptotic efficiency improves as the magnitude of the covariate effect increases. An economic application of the money demand equation is provided.

• Journal of Applied Reliability
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• 제3권2호
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• pp.117-125
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• 2003

In sampling survey, prior-information about population has been generally ignored to estimate parameters. But if there is some believable prior-information about population, it is very useful to get more efficiency estimators by using the prior-information. This paper shows how to estimate the parameter, to evaluate the variance of the estimator, and to un-biasness of the estimator by using multiple stratification with prior-information about survey population. The proposed method is illustrated with a set of hypothetical data. The results show that the proposed estimator is very efficiency and strongly recommendable.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제23권5호
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• pp.1270-1281
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• 1998

Frequency offset in an orthogonal frequency division multiplexing (OFDM) system is known to cause the inter-channel interference (ICI), amplitude and phase distortion of a received signal, resulting in a severe performance degradation of the total system. In this paper, we propose an improved pilot-based masimum likelihood frequency offset estimation technique, which uses the predefined sync-subchannels, and derive the error performance of the proposed frequency offset estimator analytically. The proposed technique improves the performance of the frequency offset estimator by adding up the frequency offset caused by coherent phase changes and averaging out the effect caused by random phase error. It is confirmed by computer simulations that the upper bound of error variance for the proposed frequency offset estimator analytically derived in this paper is correct, and that the proposed estimator has better performance than the previous ones in terms of error variance, tracking range, and time-varying characteristics of a channel.