• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.837-842
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• 2008

Students taking linear model courses have difficulty in determining which parametric functions are estimable when the design matrix of a linear model is rank deficient. In this note a special form of estimable functions is presented with a linear combination of some orthogonal estimable functions. Here, the orthogonality means the least squares estimators of the estimable functions are uncorrelated and have the same variance. The number of the orthogonal estimable functions composing the special form is equal to the rank of the design matrix. The orthogonal estimable functions can be easily obtained through the singular value decomposition of the design matrix.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.473-481
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• 2001

Shapiro and Wilk (1972) developed a test for exponentiality with origin and scale unknown. The procedure consists of comparing the generalized least squares estimate of scale with the estimate of scale given by the sample variance. However the test statistic is inconsistent. Kim(2001) proposed a modified Shapiro-Wilk's test statistic based on the ratio of tow asymptotically efficient estimates of scale. In this paper, we study the asymptotic behavior of the statistic using the approximation of the quantile process by a sequence of Brownian bridges and represent the limit null distribution as an integral of a Brownian bridge.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.765-776
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• 2006

In this paper we propose an estimation method on the regression model with randomly censored observations of the training data set. The weighted least squares support vector machine regression is applied for the regression function estimation by incorporating the weights assessed upon each observation in the optimization problem. Numerical examples are given to show the performance of the proposed estimation method.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.25-32
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• 1999

A single outlier can influence on the least squares estimators and can invalidate analysis based on these estimators. The Cook's statistic has been introduced to measure influence of individual data point on parameter estimation and the quantile of the F distribution is recommended as a reference value. but in practice subjective judgement is applied in the choice of appropriate quantile. A simple reference value is introduced in this paper which is developed by approximating conditional quantities of Cook's measure. The performance of the proposed criterion is evaluated through analysis of real data set.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.158-159
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• 2005

The paper presents a method for location of subsurface UXOs. The approach utilities gradient interpretation techniques (analytic signal, horizontal gradient and Euler methods) to locate the objects. Then, linear least-squares technique, we obtain the magnetization location of the sources. We demonstrate the practical utility of the method using marine magnetic field data.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.88-97
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• 1994

We persent a method for kinematic calibration of open chain mechanisms based on the product of exponentials (POE) formula. The POE formula represents the forward kinematics of an open chain as a product of matrix exponentials, and is based on a modern geometric interpretation of classical screw theory. Unlike the kinematic parameters in the POE formula vary smoothly with changes in the joint axes;ad hoc methods designed to address the inherent singularities in the D-H parameters are therefore are therefore unnecessary. After introducing the POE formula, we derive a least-squares kinematic calibration algorithm for general open chain mechanisms. Simulation results with a 6-axis open chain are presented.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.439-446
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• 2014

Quantile regression models with errors in variables have received a great deal of attention in the social and natural sciences. Some eorts have been devoted to develop eective estimation methods for such quantile regression models. In this paper we propose an orthogonal distance quantile regression model that eectively considers the errors on both input and response variables. The performance of the proposed method is evaluated through simulation studies.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.780-785
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• 1998

In this paper, it is shown that the conventional methods for dealing with the singularity problem of a manipulator can be generalized as a local minimization problem with differently weighted objective functions. A new damping method proposed in this article automatically determines the damping amounts for singular values, which are inversely proportional to the magnitude of the singular values. Furthermore, this can be done without explicitly computing the singular values. The proposed method can be applied to all the manipulators with revolute joints.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.254-262
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• 1990

A predictive functional relationship model is presented for the calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the ordinary least squares and maximum likelihood estimation methods are considered, while for the prediction of unknown standard measurementswe consider direct and inverse approaches. Relative performances of those calibration procedures are compared in terms of the asymptotic mean square error of prediction.

• Communications for Statistical Applications and Methods
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• v.3 no.1
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• pp.257-265
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• 1996

We consider nonstationary autoregressive autoregressive process with infinite variance of error. In the case of infinite cariance, the limiting distribution of the estimated coefficient is different from that under the finite cariance assumption. In this paper we show that the bootstrap method can be used to approximate the distribution of ordinary least squares estimator of the coefficient in the first order random walk process with infinite variance through some empirical studies and we suggest a test procedure based on bootstrap method for the unit root test.