• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.13-24
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• 2001

In this paper, we investigated mean estimation methods in two-phase sampling. Under the fixed expected cost we reviewed the optimal sample sizes, minimum variances and approximate unbiased variance estimators for usual ratio estimator, stratified sample mean with proportional allocation and Rao's allocation of the second phase sample. Also we proposed combined ratio estimator, which uses both ratio estimation and stratification and derived optimal sample size, minimum variance and unbiased variance estimator. Through a limited simulation study, we compared estimators by design effects and came to know that ratio estimator is more efficient than stratified sample mean in some cases and inefficient in the other cases, but combined ratio estimator is more efficient than others in most cases.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.449-462
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• 2016

This paper considers a long-run variance estimation using a block bootstrap method under strong dependence also known as long range dependence. We extend currently available methods in two ways. First, it extends bootstrap methods under short range dependence to long range dependence. Second, to accommodate the observation that strong dependence may come from deterministic trend plus noise models, we propose to utilize residuals obtained from the nonparametric kernel estimation with the bimodal kernel. The simulation study shows that our method works well; in addition, a data illustration is presented for practitioners.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.93-99
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• 2011

This paper proposes a novel network jitter estimation algorithm for robust VoIP communication system. The proposed method computes the current network environment mode using the differences of arrival time and generation time from sequential received packets. According to the current network environment mode, the jitter variance weights is adjusted to minimize the error for estimating the network jitter. The jitter average and variance are calculated by the autoregressive estimated algorithm, and then the network jitter is estimated by applying the jitter variance weights.

• Journal of Korean Society for Quality Management
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• v.12 no.2
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• pp.11-14
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• 1984

Some statistics are presented for construction of confidence intervals of variance components for the unbalanced twofold nested classification model and they are shown to be approximated by chi-square distributions.

• Journal of the Korean Statistical Society
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• v.32 no.2
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• pp.103-119
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• 2003

Properties of stochastic regression imputation are discussed under the uniform within-cell response model. Variance estimator is proposed and its asymptotic properties are discussed. A limited simulation is also presented.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.59-67
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• 1991

The hazard estimator is proposed for estimating system failure probability of a general network where all minimal cut sets are given. Theoretical variance of the hazard estimator is derived in a bridge system. It is demonstrated that variance of the hazard estimator is much smaller than that of the raw simulation estimator particularly for small arc failure probability.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.361-370
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• 2003

Those who are interested in making inferences concerning linear combination of valiance components in a simple linear regression model with unbalanced nested error structure can use the confidence intervals proposed in this paper. Two approximate confidence intervals for the sum of two variance components in the model are proposed. Simulation study is peformed to compare the methods. The methods are applied to a numerical example and recommendations are given for choosing a proper interval.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.55-63
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• 1989

In this paper we present the shrunken testing estimator for the variance of normal population and we find the condition that can be used in seeking the situations in which the proposed estimator is superior to the minimum variance unbiased estimator.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.249-259
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• 2002

In order to estimate the mean and variance for a Normal distribution which is truncated at both right and left sides, maximum likelihood estimators based on the entire sample from the original distribution are compared with the sample mean and variance of the censored sample which is the data remaining after truncation using simulation. We found that, surprisingly, the mean squared error of the mean based on the censored data Is smaller than that of the full sample estimators.

• Journal of the Korean Statistical Society
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• v.9 no.1
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• pp.97-108
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• 1980

Variance components model appears often in designing experiments including time series data analysis. This paper is investigating the properties of the various procedures in estimating variance components for the two-way random model without interaction under normality. In this age of computer-oriented computations, MINQUE is found to be quite practicla because of the robustness with respect to the design configurations and parameters. Also adjusted AOV type estimation procedure is found to yield superior results over the unadjusted one.