• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.421-444
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• 1994

Reliability acceptance sampling is concerned with whether to accept or reject a collection of items based upon the information obtained from life testing. Although various reliability acceptance sampling plans have been developed, little is known about their relatvie performances. This paper compares reliability acceptance sampling plans under Type II censoring, Hybrid censoring, and Time-Truncated Type II censoring assuming that the lifetimes of items in a lot follow an exponential distribution. The three plans are compared in terms of the power, the expected number of failures, and the expected time required to reach a decision. Computational experiments are conducted and the results are tabulated to provide guidelines for selecting an appropriate plan for a given situation.

• Communications for Statistical Applications and Methods
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• v.14 no.2
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• pp.355-363
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• 2007

In this paper a Bayesian estimation of the two-parameter kappa distribution was discussed under the noninformative prior. The Bayesian estimators are obtained by the Gibbs sampling. The generation of the shape parameter and scale parameter in the Gibbs sampler is implemented using the adaptive rejection Metropolis sampling algorithm of Gilks et al. (1995). A Monte Carlo study showed that the Bayesian estimators proposed outperform other estimators in the sense of mean squared error.

• Communications for Statistical Applications and Methods
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• v.23 no.1
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• pp.47-55
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• 2016

Stratified cluster sampling has been widely used for effective parameter estimations due to reductions in time and cost. The probability proportional to size (PPS) sampling method is used when the number of cluster element are significantly different. However, simple random sampling (SRS) is commonly used for simplicity if the number of cluster elements are almost the same. Also it is known that the ratio estimator produces a good performance when the total number of population elements is known. However, the two stage cluster estimator should be used if the total number of elements in population is neither known nor accurate. In this study we suggest a composite estimator by combining the ratio estimator and the two stage cluster estimator to obtain a better estimate under a certain population circumstance. Simulation studies are conducted to compare the superiority of the suggested estimator with two other estimators.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.541-547
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• 1992

The phased array antenna has the ability to perform adaptive sampling by directing the radar beam without inertia in any direction. The adaptive sampling capability of the phased array antenna allows each sampling time interval to be varied for each target, depending on the acceleration of each target at any time. In this paper we design a three-dimensional adaptive tracking algorithm for the phased array radar system with a given set of measurement parameters. The tracking algorithm avoids taking unnecessarily frequent samples, while keeping the angular prediction error within a fraction of antenna beamwidth so that the probability of detection will not be degraded during a track update illuminations. In our algorithm, the target model and the sampling rate are selected depending on the target range and the target maneuver status which is determined by a maneuver detector. A detailed simulation is conducted to test the validity of our tracking algorithm for encounter geometries under various conditions of maneuver.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.11
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• pp.67-72
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• 2011

In this paper, we investigate the energy detector to detect a primary user. And employ the compressed sensing method to get the lower sampling rate than Nyquist sampling rate. In more wide bandwidth we using the small samples than Nyquist sampling rate samples to recover original signal. we investigate the performance of energy detector with compressive sensing method under suzuki channel. The performance is investigated by simulation and compared to that of conventional energy detector.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.643-652
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• 2019

We propose a method for sample size determination using design effect formulas when a sample is resigned for a repeated survey. The proposed method enables the determination of the sample size by incorporating the impact of various design components to the sampling error through design effect formulas that are applicable under multistage sampling design and stratified multistage sampling designs.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.495-509
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• 2015

We study a classification problem of significant differences in the proportion of two groups known as the unbalanced classification problem. It is usually more difficult to classify classes accurately in unbalanced data than balanced data. Most observations are likely to be classified to the bigger group if we apply classification methods to the unbalanced data because it can minimize the misclassification loss. However, this smaller group is misclassified as the larger group problem that can cause a bigger loss in most real applications. We compare several classification methods for the unbalanced data using sampling techniques (up and down sampling). We also check the total loss of different classification methods when the asymmetric loss is applied to simulated and real data. We use the misclassification rate, G-mean, ROC and AUC (area under the curve) for the performance comparison.

• Asian Journal for Public Opinion Research
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• v.3 no.4
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• pp.156-175
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• 2016

This paper considers whether random sampling always produces more accurate survey results in the case of South Korea. We compare information from the 2010 census to the demographic variables of three public opinion surveys from South Korea: Gallup Korea's Omnibus Survey (Survey A) is conducted every two months by Gallup Korea; the annual Social Survey (Survey B) is conducted by Statistics Korea (KOSTAT); the Korean General Social Survey (KGSS or Survey C) is conducted annually by the Survey Research Center (SRC) at Sungkyunkwan University (SKKU). Survey A uses quota sampling after randomly selecting the neighborhood and initial addresses; Survey B uses random sampling, but allows replacements in some situations; Survey C uses simple random sampling. Data from more than one year was used for each survey. Our analysis suggests that Survey B is the most representative in most respects, and, in some respects, Survey A may be more representative than Survey C. Data from Survey C was the least stable in terms of representativeness by geographical area and age. Single-person households were underrepresented in both Surveys A and C, but the problem was more severe in Survey A. Four-person households and married persons were both over-represented in Survey A. Less educated people were under-represented in both Survey A and Survey C. There were differences in income level between Survey A and Survey C, but income data was not available for Survey B or the census, so it is difficult to ascertain which survey was more representative in this case.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1286-1295
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• 2007

This paper proposes, based on a bandpass sampling theory, a novel method to find valid sampling frequency range and minimum sampling rate with low computational complexity for downconversion of N bandpass radio frequency(RF) signals, under application of all possible signal placements(full permutations) in a IF stage. Additionally, we have developed a complexity-reducing method to obtaine the opttimal and minimal sampling rate for supporting the user-wanted guard-band or spacing between adjacent downconverted signal spectrums. Moreover, we have verified through comparisons with other methods that the proposed methods have more advantageous properties.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.78-78
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• 1994