• Journal of the Korean Statistical Society
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• v.8 no.2
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• pp.99-105
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• 1979

In Thoman and Bain and Schafer and Sheffield, procedures for testing the equality of the scale parameters of two Weibull populations with a common shape parameter and procedures for selecting the Weibull population with the largest scale parameter are given. We give, in this paper, a modified procedure for the above testing and selection problems, which is more powerful than those previoulsy given.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.311-316
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• 1991

This paper deals with designing the PID autotuner. The system parameters are identified using the relay control, where the unidirectional relay with hysteresis is adopted. The digital PID tuning rule on Nyquist plot is derived, and the statistical wordlength is adopted for the coefficient wordlength. The experimental results of temperature control exhibit the satisfactory performance and the validity of the derived statistical wordlength.

• Journal of the Korean Statistical Society
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• v.2 no.1
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• pp.3-7
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• 1973

Zellner, Kmenta, Dreze (1966) and later Hedges (1969) showed that consistent estimates of the parameters of Cobb-Douglas or CES production functions can be obtained by the single equation estimation methods if the models incorporate the assumption that firms maximize the mathematical expectation of profits. This note demonstrates that the results of the above-cited works can be extended to a class of VES production function models.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.15-27
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• 2001

One proposal is made for constructing nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of idea of Johns for estimating the center of the symmetric distribution together with the idea of regression quantiles and regression trimmed mean. This nonparametric estimator and some other L-estimators are studied by Monte Carlo.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.94-100
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• 1995

Vector autoregressive process disturbed by measurement error is a vector autoregressive process with nonlineat parametric restrictions on the parameter. A Newton-Raphson procedure for estimating the parameter which take advantage of the information contained in the restrictions is proposed.

• Journal of the Korean Statistical Society
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• v.34 no.1
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• pp.35-38
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• 2005

A single, tractable, special case of the problem of continuous mixtures of beta distributions over their parameters is considered. This is the uniform mixture of generalized arc-sine distributions which, curiously, turns out to be linked by transformation to the Cauchy distribution.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.99-111
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• 1995

It is shown that the adaptive kernel methods can potentially produce superior density estimates to the fixed one. In using the adaptive estimates, problems pertain to the initial choice of the estimate can be solved by iteration. Also, simultaneous recommended for variety of distributions. Some data-based method for the choice of the parameters are suggested based on simulation study.

• Journal of the Korean Statistical Society
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• v.7 no.2
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• pp.105-108
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• 1978

Freund, Vail, and Ross, Goldberger and Jochems and Goldberger have given some results for the stepwise estimation of the parameters of a univariate regression model, D.G. Kabe gave similar results for a multivariate linear regression model. We give here alternative derivation of some results derived by D.G. Kabe.

• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.221-235
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• 1998

Suppose that an observed process can be written as the additive model of the signal process and the noise process with unknown parameters. In practice the signal process is not directly observed. We consider the problem of estimating parameter from the observation process using the quasi-likelihood method.

• Journal of the Korean Statistical Society
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• v.18 no.2
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• pp.97-106
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• 1989

We consider two semiparametric regression lines where the density of the error terms are unknown. We give simultaneous estimatros of the differences of intercepts and slopes which turn out to be asymptotically minimax as well as efficient in semiparametric sense.