• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.9
• /
• pp.909-917
• /
• 1992

This paper proposes the realization of state-space digital filters with minimum output error variance. The algorithm is transforms of controllability and observability gramian in linear time invariant systems by weighted function and can improve performance of the digital filters by reducing the put error variance for state space coeffient variation. A numerical example shows that algorithm structure has much lower output error variance than that of other four structures(canonical, parallel, statistical sensitivity, balanced).

• Spatial Information Research
• /
• v.8 no.2
• /
• pp.243-255
• /
• 2000

The spatial distribution characteristics and patterns of geographic features in space can be understood through a variety of analysis techniques. The scale is one of most important factors in spatial analysis techniques. This study is aimed at identifying the characteristics of spatial data with a coarser spatial resolution and finding procedures for spatial resolution in operational scale. To achieve these objectives, this study selected LANSAT TM imagery for Sunchon Bay, a coastal wetland for a study site, applied the indices for representing scale characteristics with resolution, and compared those indices. Local variance and fractal dimension developed by previous studies were applied to measure the textual characteristics. In this study, Moran s I was applied to measure spatial pattern change of variance data which were generated from the process of coarser resolution. Drawing upon the Moran s I of variancedata was optimum technique for analysing spatial structure than those of previous studies (local variance and fractal dimension). When the variance data represents maximum Moran´s I at certainly resolution, spatial data reveals maximum change at that resolution. The optimum resolution for spatial data can be explored by applying these results.

• The Korean Journal of Applied Statistics
• /
• v.29 no.4
• /
• pp.595-611
• /
• 2016

We use nonlinear regression models (such as the Hill Model) when we analyze data in toxicology and/or pharmacology. In nonlinear regression models an estimator of parameters and estimation of measurement about uncertainty of the estimator are influenced by the variance structure of the error. Thus, estimation methods should be different depending on whether the data are homoscedastic or heteroscedastic. However, we do not know the variance structure of the error until we actually analyze the data. Therefore, developing estimation methods robust to the variance structure of the error is an important problem. In this paper we propose a method to estimate parameters in nonlinear regression models based on a preliminary test. We define an estimator which uses either the ordinary least square estimation method or the iterative weighted least square estimation method according to the results of a simple preliminary test for the equality of the error variance. The performance of the proposed estimator is compared to those of existing estimators by simulation studies. We also compare estimation methods using real data obtained from the National Toxicology program of the United States.

• International Journal of Advanced Culture Technology
• /
• v.7 no.1
• /
• pp.237-242
• /
• 2019

Spark variance technique is melded the jagged spill-over-sonance status of the glitter-differentiation knowledge level (GDKL) on the spark knowledge gestalt. The knowledge level condition by the spark knowledge gestalt system is comprised with the spill-over-sonance system. As to search a spot of the glitter situation, we are obtained of the spark value with black-red dot by the spill-over upper structure. The concept of knowledge level is comprised the reference of glitter-differentiation level for variance signal by the spark sonance gestalt. Further presenting a jagged variance of the GDKL of the maximum in terms of the spill-over-sonance gestalt, and spark spot sonance that was the a spark value of the far variance of the Spa-kg-FA-${\rho}_{MAXN}$ with $17.68{\pm}2.22units$, that was the a spark value of the convenient variance of the Spa-kg-CO-${\rho}_{MAXN}$ with $7.55{\pm}0.59units$, that was the a spark value of the flank variance of the Spa-kg-FL-${\rho}_{MAX}$ with $2.70{\pm}0.48units$, that was the a spark value of the vicinage variance of the Spa-kg-VI-${\rho}_{MAX}$ with $0.48{\pm}0.05units$. The spill-over sonance will be to appraisal at the jagged ability of the spill-over-sonance gestalt with black-red dot by the spark knowledge level on the GDKL that is presented the glitter-differentiation gestalt by the knowledge level system. Spill-over knowledge system will be possible to restrain of a gestalt by the special signal and to employ a spark data of spill-over sonance level.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.4
• /
• pp.767-778
• /
• 2003

This paper presents a method for generating optimal fuzzy rules using a genetic algorithm. Fuzzy rules are generated from the training data in the first stage. In this stage, fuzzy c-Means clustering method and cluster validity are used to determine the structure and initial parameters of the fuzzy inference system. A cluster validity is used to determine the number of clusters, which can be the number of fuzzy rules. Once the structure is figured out in the first stage, parameters relating the fuzzy rules are optimized in the second stage. Weights and variance parameters are tuned using genetic algorithms. Variance parameters are also managed with left and right for asymmetrical Gaussian membership function. The method ensures convergence toward a global minimum by using genetic algorithms in weight and variance spaces.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 1998.11a
• /
• pp.253-258
• /
• 1998

Staggered nested designs are the most popular class of unbalanced nested designs in practical fields. The most important features of the staggered nested design are that it has a very simple open-ended structure and each sum of squares in the analysis of variance has almost the same degrees of freedom. Based on the features, a class of unbalanced nested designs which is generalized of the staggered nested design is proposed. Some of the generalized staggered nested designs are shown to be more efficient than the staggered nested design in estimating some of variance components and their linear combinations.

• Korean Management Science Review
• /
• v.11 no.2
• /
• pp.29-41
• /
• 1994

This paper analyses the stochastic nature of the Permanent Income Hypothesis (PIH) by specifying the variance-covariance structure of PIH based on Hall and Mishkin[3]. Maximum likelihood is employed to estimate the model by explicitely incorporating the heteroscedastic nature of the data into the likelihood. The data used are individual Korean household consumption and income data. The results indicate that the data are generally consistent with the Permanent Income Hypothesis, and about 11 percent of the total variation in consumption may be attributable to the excess sensitivity of consumption to income.

• Journal of the Korean Statistical Society
• /
• v.24 no.2
• /
• pp.407-417
• /
• 1995

The h-plot is a graphical technique for displaying the structure of one population's variance-covariance matrix. This follows the mathematical algorithem of the principle component biplot based on the singular value decomposition. But it is known that the singular value decomposition is not resistant, i.e., it is very sensitive to small changes in the input data. In this article, since the mathematical algorithm of the h-plot is equivalent to that of principal component biplot of Choi and Huh (1994), we derive the resistant h-plot.

• The Journal of Industrial Distribution & Business
• /
• v.8 no.1
• /
• pp.5-13
• /
• 2017

Purpose - In this article, a dynamic model like a VAR is an appropriate choice for estimating the possible interrelationship between ownership structure and firm performance as a dynamic process. Research design, data, and methodology - Data of this work are collected from Chinese stock exchange including 350 Chinese-listed firms during the period of 1999-2012. We hypothesize that this interrelationship dynamically exists between ownership structure and firm performance. To examine the correlation, a panel Vector Auto-regression (PVAR) approach generated by GMM method is utilized to test the possible dynamic relation embedded in corporate governance. Another two dynamic analysis solutions such as orthogonalized impulse-response function and variance decomposition are also used simultaneously. Results - Findings of this study indicate the evidence that dynamically endogenous relationship exists between ownership structure and firm performance. Further, there is a dynamical correlation between investment and performance. Impulse response and variance decomposition illustrate that impact of a shock to variables themselves is the main source for their variability. Conclusions - The conclusion in this study is that there is a bidirectional and inter-temporal effect between proportion of ownership and corporate performance for a long run in accordance with impulse response function. Overall, our results suggest that corporate governance in China is more market oriented.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1991.10a
• /
• pp.57-62
• /
• 1991

For the purpose of developing the method for efficiently calculating the design sensitivity and the reliability for the complicated structure such as ship structure, the probabilistic finite element method is introduced to formulate the deterministic design sensitivity analysis method and incorporated with the second moment reliability methods such as MVFOSM, AFOSM and SORM. Also, the probabilistic design sensitivity analysis needed in the reliability-based design is performed. The reliability analysis is carried out for the initial yielding failure, in which the derivative derived in the deterministic desin sensitivity is used. The present PFEM-based reliability method shows good agreement with Monte Carlo method in terms with the variance of response and the associated probability of failure even at the first or first few iteration steps. The probabilistic design sensitivity analysis evaluates explicitly the contribution of each random variable to probability of failure. Further, the reliability index variation can be easily predicted by the variation of the mean and the variance of the random variables.