• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.465-475
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• 2013

Higher quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. Usually, the quality level is measured by process capability indices. The index is used to determine whether a production process is capable of producing items within a specified tolerance. Some useful process capability indices $C_p$, $C_{pk}$ and $C_{pm}$ have been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. It is necessary to investigate their asymptotic correlationship among process capability indices $\hat{C}_p$, $\hat{C}_{pk}$ and $\hat{C}_{pm}$. In this paper, we study their asymptotic correlationship for some process capability indices $\hat{C}_p$, $\hat{C}_{pk}$ and $\hat{C}_{pm}$ under the normal process.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.301-308
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• 2016

The process capability index is used to determine whether a production process is capable of producing items within a specified tolerance. Some process capability indices $C_p$, $C_{pk}$ and $C_{pm}$ have been of particular interest as useful management tools for tracking process performance. Most evaluations on process capability indices focus on statistical estimation and test of hypothesis. It is necessary to investigate their asymptotic correlationship among basic estimators ${\hat{C}}_p$, ${\hat{C}}_{pk}$ and ${\hat{C}}_{pm}$ of process capability indices $C_p$, $C_{pk}$ and $C_{pm}$. In this paper, we study their asymptotic correlationship for three process capability indices ${\hat{C}}_p$, ${\hat{C}}_{pk}$ and ${\hat{C}}_{pm}$ under bivariate normal distribution BN(${\mu}_x,{\mu}_y,{\sigma}^2_x,{\sigma}^2_y,{\rho}$). With some nonnormal processes, the asymptotic correlation coefficient of any two respective process capability index estimators could be established.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.61-73
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• 2016

We consider the wild bootstrap Ljung-Box (LB) test for autocorrelation in residuals of fitted multivariate time series models. The asymptotic chi-square distribution under the IID assumption is traditionally used for the LB test; however, size distortion tends to occur in the usage of the LB test, due to the conditional heteroskedasticity of financial time series. In order to overcome such defects, we propose the wild bootstrap LB test for autocorrelation in residuals of fitted vector autoregressive and error correction models. The simulation study and real data analysis are conducted for finite sample performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.374-378
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• 2003

The asymptotic performance of the two-sample locally optimum rank detector for random signals buried in signal-dependent noise and additive noise is consigered in this paper. It is shown that the locally optimum rank detector, a nonparametric detector, has reasonable asymptotic performance for a class of correlated random signals, compared with the locally optimum detector. It is noteworthy that the the two-sample locally optimum rank detector perform almost the same with the one-sample locally optimum rank detector.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.529-545
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• 2023

This paper introduces the Banded-VHAR model suitable for high-dimensional long-memory time series with band structure. The Banded-VHAR model has nonignorable correlations only with adjacent dimensions due to data features, for example, geographical information. Row-wise estimation method is adapted for fast computation. Also, two estimation methods, namely BIC and ratio methods, are proposed to estimate the width of band. We demonstrate asymptotic consistency of our proposed estimation methods through simulation study. Real data applications to pm2.5 and apartment trading volume substantiate that our Banded-VHAR model outperforms traditional sparse VHAR model in forecasting and easy to interpret model coefficients.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.5
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• pp.19-27
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• 2004

A delay dependent fuzzy $H_2/H_{\infty}$ controller design method for delayed fuzzy dynamic systems is considered. Using delay-dependent Lyapunov function, the asymptotical stability and $H_2/H_{\infty}$ performance problem are discussed. A sufficient condition for the existence of fuzzy controller is presented in terms of linear matrix inequalities(LMIs). A simulation example is given to illustrate the design procedures and performances of the proposed methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1682-1685
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• 2005

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolerance of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or estimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte-Carlo Method and got the probabilistic sensitivity. The sensitivity of structural response with respect to inconstant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Journal of the Korean Geosynthetics Society
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• v.15 no.2
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• pp.65-75
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• 2016

In this study, we constructed a database by collecting field pullout test data of the soil nailing using pressurized grouting, and suggested a method to estimate the ultimate pullout resistance using nonlinear regression analysis to overcome the problems of ultimate pullout resistance estimation using graphical methods. The load-displacement curve estimated by nonlinear regression showed a very high correlation with the field pullout test data. Estimated ultimate pullout load by nonlinear regression method was average 29% higher than estimated ultimate pullout load using previous graphical method. A sigmoidal growth model was found to be the best-fitting nonlinear regression model against rapid pullout failure. Further, an asymptotic regression model was found to be the best fit against progressive nail pullout. The unit ultimate skin friction suggested in this research reflected in the domestic geotechnical characteristics and the specifications of the pressurized grouting method. This research is expected to contribute towards establishing an independent design standard for the soil nailing by providing solutions to the problems that occur when using design charts based on foreign research.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.424-429
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• 2019

The evolution of networking technology such as commercialization of 5G systems provides foundation for information exchange and control of systems over the network. In addition, importance of controlling a system with delay is increasing significantly, since various phenomena in the network are associated with delay. In this paper, with a predictive control which has been studied for designing a controller with low complexity, we propose a novel predictive control for a system with multi-inputs such that it can keeps the complexity almost the same regardless of the number of inputs and degree of delay. The asymptotic stability of the proposed control with a static output feedback is also proved. The numerical simulation shows that the proposed method is superior in complexity and the performance of finding feasible controllers to the existing predictive control and a conventional method based on augmented states.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8C
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• pp.709-712
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• 2010

In this paper, the two sample locally optimum rank detector is obtained in the weakly dependent noise with non-zero temporal correlation between noise observations. The test statistic of the locally optimum rank detector is derived from the Neyman-Pearson lemma suitable for the two sample observation models, where it is assumed that reference observations are available in addition to regular observations. Two-sample locally optimum rank detecter shows the same performance with the one-sample locally optimum rank detector asymptotically. The structure of the two-sample rank detector is simpler than that of the one-sample rank detector because the sign statistic is not processed separately.