• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.531-541
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• 1997

The asymptotic distribution of residual autocorrelation functions from a generalized p-order random coefficient autoregressive process (GRCA(p)) is derived. To this end, we first describe the GRCA(p) models and then consider the normalised residuals after fitting the model. This result can be applied to the residual analysis for the diagonostic purpose.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.233-237
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• 2003

An asymptotic property of the ordinary least squares estimator of the disturbance variance is considered in the regression model with correlated errors. It is shown that the convergence in probability of S$^2$ is equivalent to the asymptotic unbiasedness. Beyond the assumption on the design matrix or the variance-covariance matrix of disturbances error, the result is quite general and simplify the earlier results.

• Journal of The Korean Association For Science Education
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• v.25 no.2
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• pp.111-121
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• 2005

The purpose of this study was to analyze characteristics of experimental design and evidence choice of the elementary school students in problem solving process related to controlling variable. For this study, 96 6th grade students were selected and tested with Science Reasoning Task. This study revealed that the types of experimental design were categorized as variance of control variable, controlling of causal variable, perfect controlling variable, imperfect controlling variable, variance of all variable. Prior belief had a strong influence on student's experimental design. The types of evidence choice were categorized as perfect controlling variable, controlling causal variable, variance of causal variable. The degree of controlling variable in evidence choice process was much lower than that in experimental design. Most students tended to choose evidence according to prior belief without controlling variable. The results of this study implied that student's prior belief and characteristic of science process skills should be considered to develop program for promoting controlling variable ability.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.77-88
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• 1999

A new measure of the process capability index(PCI) $\textit{C}_{cpk}$ is proposed that takes into account the proximity to the target value as well as process mean and process variation when we assessing process performance. using the semivariance estimators proposed by Choobineh and Branting (1986) and Josephy and Aczel (1993) the estimator($\textit{C}_{cpk}$) of new index has been solved and the properties of these estimators have been examined through simulations. Also we compare the performance between $\textit{C}_{cpk}$ and $\textit{C}_{jpk}$ which is developed by Johnson kotz and Pearn(1992).

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.191-196
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• 2005

Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose a MLE of the process change point when control charts with the fixed sampling rate (FSR) scheme or the variable sampling rate (VSR) scheme monitor a process to detect changes in the process mean and/or variance of a normal quality variable.

• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.68-79
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• 2009

A variance map can be used to detect and distinguish texts from background in images. However, previous variance maps work at one level and they suffer a limitation in dealing with varieties in text size, slant, orientation, translation, and color. We present a method for robustly segmenting text regions in complex color Web images using two-level variance maps. The two-level variance maps work hierarchically. The first level finds the approximate locations of text regions using global horizontal and vertical color variances with the specific mask sizes. The second level then segments each text region using intensity variance with a local mask size, which is determined adaptively. By the second process, backgrounds tend to disappear in each region and segmentation can be accurate. Highly promising experimental results have established the effectiveness of our approach.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.109-112
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• 1989

Gun system operation is represented as a first-order Markov process, and an optimum linear filter is derived for closed-loop control of mean square error. Potential improvement is then estimated by contrasting the variance in performance and the auto correlation for open-loop system with that for the optimum linearly corrected process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.333-341
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• 1997

The purpose of this paper is to compare the manufacturing process with random covariate using multiple comparison procedure. The methodology that compares each manufacturing process by inspecting the number of nonconforming items out of k-treatment, has serveral limitations and problems according to the method and contect of the analysis. The proper way of analysis, therefore, could be obtained by the multiple comparison procedure of simultaneous confidence region of variance components. Effections that affect a manufactuing process may be predictive of responce to treatments are called covariates. In the study of comparing several treatments, prsense of covariate may bias the estimates of treatment effects.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.527-535
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• 2011

This study proposes a modified definition about $C_{pk}$ based on median as the centering parameter in order to more easily control the process since the mean does not represent any quantile of the asymmetric process distribution. Then we consider an estimate and derive the asymptotic normality for the estimate of the modified $C_{pk}$. In addition, we provide an example with asymmetric distributions and discuss the estimation for the limiting variance that are followed by some concluding remarks.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.1
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• pp.14-20
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• 1996

This paper presents a self tuning method of a velocity type PID controller for minimum or non-minimum phase systems with time delays. The velocity type PID control structure is determined in the process of minimizing the variance of the auxilliary output, and self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design parameter. This method is simple and effective compared with other existing methods[1,2]. Numerical examples are included to illustrate the procedure and to show the performance of the control system.