• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.1-13
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• 2018

In many studies, a researcher attempts to describe a population where units are measured for multiple outcomes, or responses. In this paper, we present an efficient procedure based on ranked set sampling to estimate and perform hypothesis testing on a multivariate mean. The method is based on ranking on an auxiliary covariate, which is assumed to be correlated with the multivariate response, in order to improve the efficiency of the estimation. We showed that the proposed estimators developed under this sampling scheme are unbiased, have smaller variance in the multivariate sense, and are asymptotically Gaussian. We also demonstrated that the efficiency of multivariate regression estimator can be improved by using Ranked set sampling. A bootstrap routine is developed in the statistical software R to perform inference when the sample size is small. We use a simulation study to investigate the performance of the method under known conditions and apply the method to the biomarker data collected in China Health and Nutrition Survey (CHNS 2009) data.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.171-180
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• 2016

Basel committee suggests using Value-at-Risk (VaR) and expected shortfall (ES) as a measurement for market risk. Various estimation methods of VaR and ES have been studied in the literature. This paper compares semi-parametric methods, such as conditional autoregressive value at risk (CAViaR) and conditional autoregressive expectile (CARE) methods, and a Gaussian quasi-maximum likelihood estimator (QMLE)-based method through back-testing methods. We use unconditional coverage (UC) and conditional coverage (CC) tests for VaR, and a bootstrap test for ES to check the adequacy. A real data analysis is conducted for S&P 500 index and Hyundai Motor Co. stock price index data sets.

• Journal of the Korean Statistical Society
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• v.29 no.1
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• pp.45-62
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• 2000

Rotation design is a sampling technique to reduce response burden and to estimate the population characteristics varying in time. Park and Kim(1999) discussed a generation of one-level rotation design which is called as {{{{r_1^m ~-r_2^m-1}}}} design has more applicable form than existing before. In the structure of {{{{r_1^m ~-r_2^m-1}}}} design, we derive the exact variances of generalized composite estimators for level, change and aggregate level characteristics of interest, and optimal coefficients minimizing their variances. Finally numerical examples are shown by the efficiency of alternative designs relative to widely used 4-8-4 rotation design. This is continuous work of Part Ⅰ studied by Park and Kim(1999).

• Journal of Sensor Science and Technology
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• v.28 no.4
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• pp.216-220
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• 2019

In this paper, we propose a finite memory filter (estimator) for discrete-time stochastic linear systems with delays in state and measurement. A novel filtering algorithm is designed based on finite memory strategies, to achieve high estimation accuracy and stability under parametric uncertainties. The new finite memory filter uses a set of recent observations with appropriately chosen initial horizon conditions. The key contribution is the derivation of Lyapunov-like equations for finite memory mean and covariance of system state with an arbitrary number of time delays. A numerical example demonstrates that the proposed algorithm is more robust and accurate than the Kalman filter against dynamic model uncertainties.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4A
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• pp.434-439
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• 2008

This paper proposes an efficient coarse frequency synchronizer for digital video broadcasting - second generation (DVB-S2). The input signal requirement of acquisition range for coarse frequency estimator in the DVB-S2 is around ${\pm}1.5625Mhz$, which corresponds to 6.25% of the symbol rate at 25Mbaud. At the process of analyzing the robust algorithm among data-aided approaches, we find that the Luise & Reggiannini (L&R) algorithm is the most promising one for coarse frequency estimation with respect to estimation performance and complexity. However, it requires many multipliers and adders to compute output values of correlators. We propose an efficient architecture identifying the serial correlator with the buffer and multiplexers. The proposed coarse frequency synchronizer can reduce the hardware complexity about 92% of the direct implementation. The proposed architecture has been implemented and verified on the Xilinx Virtex II FPGA.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.97-103
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• 2019

In this paper, we designed and fabricated a receiving modem that can be applied to guided weapons can change real-time targets with little effect of fading. The designed modem consists of synchronous detector, timing error estimator, timing recovery, differential decoder and viterbi decoder, and it's implemented in FPGA so that it can be redesigned and modified according to requirements. The modem board was directly converted from IF frequency to baseband and converted into digital data through ADC. It is confirmed that it is applicable to the guided weapons that changing real-time targets through simulations, measurements and test.

• Journal of Integrative Natural Science
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• v.11 no.3
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• pp.154-160
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• 2018

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p-r{\geq}3)$, r = rank(K) with a projection matrix K under the quadratic loss, based on a sample $Y_1$, $Y_2$, ${\cdots}$, $Y_n$. In this paper a James-Stein type estimator with shrinkage form is given when it's variance distribution is specified and when the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is constrain, where K is an idempotent and symmetric matrix and rank(K) = r. It is characterized a minimal complete class of James-Stein type estimators in this case. And the subclass of James-Stein type estimators that dominate the sample mean is derived.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.71-80
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• 2007

The present paper investigates estimation of a scale parameter of a gamma distribution using a loss function that reflects both goodness of fit and precision of estimation. The Bayes and empirical Bayes estimators rotative to balanced loss functions (BLFs) are derived and optimality of some estimators are studied.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.898-902
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• 2018

A novel heart beat interval estimation algorithm is presented based on parabola approximation method. This paper presented a two-step processing scheme; a first stage is finding R-peak in the Electrocardiogram (ECG) by Shannon energy envelope estimator and a secondary stage is computing the interpolated peak location by parabola approximation. Experimental results show that the proposed algorithm performs better than with the previous method using low sampled ECG signals.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.361-364
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• 2001

This paper presents a simple method for estimating the maximum crosstalk noise of on-chip grobal wires. For the derivation of the maximum crosstalk expression we have modeled wires using lumped-elements that are composed of R, L and C. We have also used experimental constant to reduce the modeling error. The accuracy of the proposed method is verified by comparing against the HSPICE simulation results under the present process parameters and environmental conditions. The results of the proposed method can be used as an estimator in design-aid tools.